Analysis of the gut microbiome during pregnancy in T1D 16S rRNA (MiSeq)
Alexandra Roth Schulze
2020-02-26
1 Background
This report shows the analysis performed for 16S rRNA gene amplicon sequencing from the gut microbiome of 148 pregnant women. For each pregnant woman, samples were taken at different time points (i.e. from 1 to 3 different time points per woman) during the pregnancy (i.e. up until day ~280 when the child is born) to give a total of 377 samples. From the 148 pregnant women, 92 are diabetic (T1D) and 56 are healthy (nonT1D). Samples from the different women were NOT taken in the exact same Day in pregnancy, thus Day should be treated as a continuous variable rather than a categorical. However, time points could be categorised into trimesters if necessary, correspondence being:
Trimester 1 = 0-99 days
Trimester 2 = 100-196 days
Trimester 3 = 196-280 days
Summary:
145 pregnancies: 94 in T1D women and nonT1D=56 in wome without T1D (non-T1D).
A total of 139 women donated samples, 6 women donated samples from 2 different pregnancies giving a total a 145 pregnancies.
1-3 time points per woman per pregnancy (from day 37 to day 274 of the pregnancy).
354 samples in total: T1D=235 and nonT1D=119.
For the analysis we would explored if there is a difference in Alpha and Beta diversity between T1D and nonT1D. Furthermore, we would also identified differentially abundant operational taxonomic units (i.e. OTUs or sequence variants of the 16S rRNA that are roughly equivalent to a bacterial species) between T1D and nonT1D pregnant women.
Sample details information:
Samples were generated by PCR amplification from stool samples targeting the V4 region of the 16S rRNA gene. Each sample was sequenced twice on different sequence wells (i.e. technical sequencing replicates) from the Illumina MiSeq instrument with the paired-end 600-cycle (2 × 300) kit. Samples were sequenced in 6 different sequencing runs. Samples from the same pregnant woman at different time points were sequenced in the same run.
2 Data generation
2.1 Processing the sequences: from sequence data to feature table
The data was processed through Qiime2 (https://qiime2.org/) which is a next-generation microbiome bioinformatics platform written in python. The analysis starts with raw DNA sequencing data with the following steps and python commands that were performed for each sequencing runs separately:
- Import paired-end sequencing data into qiime2.
- command: qiime tools import –type EMPPairedEndSequences –input-path ./1-Run/ –output-path ./1-Run/1-Run_MISEQXXXX.qza
- Demultiplex data to know which sample each paired-end reads belong to.
- command: qiime demux emp-paired –m-barcodes-file metadata.tsv –m-barcodes-category BarcodeSequence –i-seqs 1-Run_MISEQXXX.qza –o-per-sample-sequences demux –p-rev-comp-mapping-barcodes
- Trimming PCR primers: Search demultiplexed paired-end sequences for adapters and remove them. In this step everything from the amplification primers on is removed.
- command: qiime cutadapt trim-paired –i-demultiplexed-sequences ./demux.qza –p-front-f GGACTACNVGGGTWTCTAAT –p-front-r GTGYCAGCMGCCGCGGTAA –o-trimmed-sequences trimmed_demux.qza –verbose
The demultiplexed data resulting from this step was uploaded to the short read archive (SRA) database (https://www.ncbi.nlm.nih.gov/sra/) with accession number PRJNA604850.
- Sequence quality control and feature table construction. In this step qiime2 uses the software Divisive Amplicon Denoising Algorithm 2 (DADA2; https://www.nature.com/articles/nmeth.3869), a quality-aware model-based approach for correcting Illumina amplicon errors. Sample composition is inferred by dividing amplicon reads into partitions consistent with the error model. DADA2 does not create OTUs (i.e. cluster sequences to a given % identity threshold) and does differentiate closely related ribosomal sequence variants (i.e. RSV or features). The complete DADA2 pipeline integrated in qiime2 implements sample inference, chimera identification, merging of paired-end reads and the creation of a “feture-per-sample counts table”.
- command: qiime dada2 denoise-paired –i-demultiplexed-seqs trimmed_demux.qza –o-table table –o-representative-sequences rep-seqs –p-trunc-len-f 230 –p-trunc-len-r 160 –p-max-ee 3 –p-n-threads 8
The 6 runs where processed with the same parameters, including trimming of the forward reads to 230 basepairs and the reverse reads to 160 bp (i.e. parameters –p-trunc-len-f 230 and –p-trunc-len-r 160) and number of expected errors higher than 3 (–p-max-ee 3). Although these parameters should be different for different sequencing runs (depending on their quality), we used the same parameters for the 6 runs (i.e. parameters from the poorest quality run were used) in order to be able to merge the resulting 6 feature tables into 1. The feature ids in the resulting tables are presented as hashes of the sequences defining each feature. The hash will always be the same for the same sequence so this allows feature tables to be merged across runs of this method. You should only merge tables if the exact same parameters are used for each run.
- The 6 tables were merged:
Command to merge feature tables: qiime feature-table merge –i-tables table_Mother_1-Run.qza –i-tables table_Mother_2-Run.qza –i-tables table_Mother_3-Run.qza –i-tables table_Mother_4-Run.qza –i-tables table_Mother_6-Run.qza –i-tables table_Mother_7-Run.qza –o-merged-table table_Mother_All-Runs.qza
Command to merge representative sequences: qiime feature-table merge-seqs –i-data rep-seq1.qza –i-data rep-seq2.qza –i-data rep-seq3.qza –i-data rep-seq4.qza –i-data rep-seq6.qza –i-data rep-seq7.qza –o-merged-data rep-seq_Allmerged.qza
Information on which samples were sequenced in which run can be found in supplementary excel file E0. If the processing using DADA2 (within Qiime2) needs to be repeated, sequences from the different sequencing runs must be processed separatelly and then the resulting tables and representative sequences must be merged previous to analysis with phyloseq.
- The taxonomic classification was done using the resulting representative sequences with the following Qiime2 command:
- qiime feature-classifier classify-sklearn –i-classifier /home/$YourPath/Naive_Bayes_classifiers/silva-119-99-515-806-nb-classifier.qza –i-reads rep-seq_Allmerged.qza –o-classification taxonomy_AllMerged.qza
- A phylogenetic tree was build within Qiime2 as follows:
- qiime alignment mafft –i-sequences rep-seq_Allmerged.qza –o-alignment aligned-rep-seq_Allmerged.qza
- qiime alignment mask –i-alignment aligned-rep-seq_Allmerged.qza –o-masked-alignment masked-aligned-rep-seq_Allmerged.qza
- qiime phylogeny fasttree –i-alignment masked-aligned-rep-seq_Allmerged.qza –o-tree unrooted-tree-rep-seq_Allmerged.qza
- qiime phylogeny midpoint-root –i-tree unrooted-tree-rep-seq_Allmerged.qza –o-rooted-tree rooted-tree-rep-seq_Allmerged.qza
Note: The phylogenetic tree was unzipped to integrated it into the phyloseq object in R. File name: Mother_All-Runs_Merged_tree.nwk
- A biom file containing the feature table, taxonomy and metadata was obtained from qiime2 unzipping the generated feature table and taxonomy:
- After unzipping table_Mother_All-Runs.qza we obtained table_Mother_All-Runs.biom, this biom file was transformed usig the software biom into a text file and then again into the correct biom format (JSON):
- biom convert -i table_Mother_All-Runs.biom -o table_Mother_All-Runs.txt –to-tsv
- biom convert -i table_Mother_All-Runs.txt -o table_Mother_All-Runs.biom –table-type=“OTU table” –to-json
The file taxonomy_AllMerged.qza containing the taxonomy was unzipped (obtaining taxonomy_AllMerged.txt) and the header “#OTUID taxonomy confidence” was added. The format of the feature classification was also changed to obtain the greengenes format (e.g. k__Bacteria; p__XXX; c__XX, etc). After this, the biom sortware was used to add the taxonomi to the biom file: *biom add-metadata –sc-separated taxonomy –observation-header OTUID,taxonomy –observation-metadata-fp taxonomy_AllMerged.txt -i table_Mother_All-Runs.biom -o table_Mother_All-Runs_wTax.biom
- The metadata (i.e. per sample information for each of the variables of factors of interest) was added:
- biom add-metadata -i table_Mother_All-Runs_wTax.biom -o table_Mother_All-Runs_wTaxMet.biom –sample-metadata-fp ./metadata_All-RunsMerged.csv
The resulting file in c) was used as input into phyloseq in order to de-identify (i.e. leave no information that could associate the samples to a person in the study) the samples prior to analysis, by replacing the metadata and saving into an R object “Mothers_OTU_AFilt1_Preg.RData”.
2.2 Processing, filtering and count normalization of feature table
The resulting R object containing the feature table, sample data and taxonomy (Mothers_OTU_AFilt1_Preg.RData), the and phylogenetic tree were imported into Phyloseq (https://github.com/joey711/phyloseq), an R package used for the preprocessing, analysis and graphical display of complex 16S rRNA amplicon data that has been already processed into a feature table. In this analysis phyloseq was used for agglomerate features into OTUs. This step was performed in a separate script: Phyloseq_Mother_data_formating_w7.R. Features that were less than 0.03% different at the sequence level were agglomerated into the same OTU based on the phylogenetic tree. After this, OTUs that had a relative abundance across all samples equal or less than 0.01% were removed. This left a total of 349 OTUs across all samples. This object was saved to Mothers_OTU_Phyloseq_Obj_Filter1_w7G.RData which was used for the analysis performed in this document.
3 Bar plots taxonomy
4 Alpha diversity
Use GEEs to account for clustering due to repeated measures, and test for differences in alpha diversity between T1D and nonT1D. Include T1D x Days interaction term to test the possibility that the change in alpha diversity over time differs between T1D and nonT1D.
‘Mean-centred’ values are being used for gestational days, age and BMI were calculated. This ensures that the model coefficients presented are meaningful. The ‘geepack’ package defaults to using the empirical (robust or ‘sandwich’) estimator, which means that the estimates are robust to misspecification of the correlation structure.
4.1 Alpha diversity (T1D vs. non-T1D continuous time [Days])
Call:
geeglm(formula = Observed ~ t1dfactor * days_c + age_c + nullip +
bmi_c + HLA, data = DivCal_R_df, id = motherid, corstr = "exchangeable")
Coefficients:
Estimate Std.err Wald Pr(>|W|)
(Intercept) 87.312304 6.321785 190.753 <2e-16 ***
t1dfactorT1D 0.598412 4.290163 0.019 0.8891
days_c -0.011349 0.027414 0.171 0.6789
age_c 0.436220 0.444266 0.964 0.3262
nullipYes -3.523319 3.718133 0.898 0.3433
bmi_c -0.619933 0.343827 3.251 0.0714 .
HLADRXX -11.273762 6.217263 3.288 0.0698 .
HLAGroup3o4 -3.854993 5.107809 0.570 0.4504
t1dfactorT1D:days_c 0.001327 0.029897 0.002 0.9646
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Estimated Scale Parameters:
Estimate Std.err
(Intercept) 539 56.69
Correlation: Structure = exchangeable Link = identity
Estimated Correlation Parameters:
Estimate Std.err
alpha 0.6766 0.05531
Number of clusters: 146 Maximum cluster size: 3 4.2 Alpha diversity (T1D vs. non-T1D categorical time [Trimesters])
Call:
geeglm(formula = Observed ~ t1dfactor * Tri + age_c + nullip +
bmi_c + HLA, data = DivCal_R_df, id = motherid, corstr = "exchangeable")
Coefficients:
Estimate Std.err Wald Pr(>|W|)
(Intercept) 87.5304 7.5855 133.15 <2e-16 ***
t1dfactorT1D 0.7492 6.2981 0.01 0.905
TriT2 -0.0419 5.2543 0.00 0.994
TriT3 -0.5486 5.6430 0.01 0.923
age_c 0.4231 0.4458 0.90 0.343
nullipYes -3.6292 3.7147 0.95 0.329
bmi_c -0.6231 0.3439 3.28 0.070 .
HLADRXX -11.2900 6.2120 3.30 0.069 .
HLAGroup3o4 -3.9233 5.1262 0.59 0.444
t1dfactorT1D:TriT2 0.2909 5.6709 0.00 0.959
t1dfactorT1D:TriT3 -0.4055 6.0407 0.00 0.946
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
Estimated Scale Parameters:
Estimate Std.err
(Intercept) 539 56.5
Correlation: Structure = exchangeable Link = identity
Estimated Correlation Parameters:
Estimate Std.err
alpha 0.676 0.0554
Number of clusters: 146 Maximum cluster size: 3 
5 OTU taxonomic level
5.1 Microbial community composition analysis at OTU level (Beta diversity analysis)
Hypothesis
Hypothesis: the gut microbiome taxonomic composition (i.e. Beta diversity) during pregnancy differs between women with and without T1D. In order to test if this hypothesis holds true, a measurement of the distance between each pair of samples is calculated (i.e. Bray-Curtis) and a repeated measure aware permutational analysis of variance (i.e. RMA-PERMANOVA) test is applied. A P-value <0.05 is considered to be significant, meaning that our hypothesis cannot be rejected. Borderline P-values are also considered positive.
Problems with the available R function for Beta diversity analysis
The current available function for performing hypothesis testing of differences in the microbiome composition between groups of samples is called Adonis (i.e. which perform a PERMANOVA test) and is part of the Rpackage vegan (Oksanen, J. et al). The main problem with this function is that if the metadata of interest does not vary with time (e.g. disease status, sex, etc.), adonis does not calculate the corresponding P value correctly, as it permutes levels within a subject. This does not make sense for something like disease status or sex as permuting within-subject will produce the exact same distribution each time you permute. This a known drawback of the adonis function for repeated measures.
In order to get the correct P-value for a time-invariant metadata, the permutation procedure has to be altered such that it permutes the subjects rather than levels within subjects, which apply to our current pregnancy dataset.
Here I’m running a script written by Jason Lloyd-Price from Curtis Huttenhower lab in Harvard. This script is being used instead of the regular Adonis (PERMANOVA test) from the R package Vegan because as stated above, our metadata of interest (i.e. T1D status) does not vary with time, we have a mixture of data which changes within and between an individual and we also have unequal group sizes (i.e. we do not always have exactly 3 samples per woman). For those three reasons, it was recommended to use his script to perform the RMA-PERMANOVA analysis.
PARAMETERS:
permute_within: This data frame has samples on rows and metadata on columns. This should only contain metadata that varies within a block (i.e. it’s a single-column data frame with only time/Days).Since, the other metadata within the block should be the same between repeated measurements and this will not hold when we introduce other factor i.e. sequencing run, BMI, parity, gestational age (i.e. Days or trimester) and conception age , those five factors should be placed here
blocks: This should just be a vector giving the group of each sample (i.e. the motherid vector; motherid is strictly accounting for personID but not for pregnancy per se).
block_data: This data frame contains per-block metadata, with one row per block (motherid). It should only contain metadata pertaining to the blocks (i.e. T1Dstatus). motherid is not numeric, ensure that the row names match the factor names in the motherid vector (blocks).
metadata_order: This is needed if you want to specify a particular order that the model should be fit in. Metadata earlier in the list will be fit and residualized first, so these should be features we are NOT interested in and want to control for.
Results from PERMANOVA test with repeat measure-aware permutations - Controlling for Days/Trimester, sequencing run, conception age, BMI, parity and HLA type
Here the blocking factor is taking into account each mother who might have given samples from different trimesters or two different pregnancies (i.e. motherid is the name of the factor). Therefore, the factor “motherid” takes into account two different pregnancies from the same mother as one SubjectID to adjust for repeated measurements
The interaction between T1D status and time was also included in order to test if the differences between T1D and non-T1D women in the same or changes throguhout pregnancy.
5.1.1 Interaction between T1D status and Time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 5 3.8 0.752 2.96 0.040 0.534
Days 1 0.3 0.255 1.01 0.003 0.113
T1D_Time_Interaction 1 1.0 1.023 4.03 0.011 0.078 .
Age 1 0.7 0.697 2.75 0.007 0.770
Parity 1 0.7 0.655 2.58 0.007 0.909
BMI 1 0.5 0.482 1.90 0.005 0.316
HLA 2 1.1 0.557 2.19 0.012 0.406
T1Dstatus 1 0.2 0.167 0.66 0.002 1.000
Residuals 340 86.4 0.254 0.914 0.856
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.078Due to the interaction between T1D and time having a significant P-value, differences in beta diversity between T1D and non-T1D was assessed by trimester using a normal PERMANOVA with the adonis function.
Note: The function relevel was used to change the trimester used as reference in the test (e.g. when testing for differences between T2 and T3).
5.1.2 T1D status in trimester 1
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.90 0.299 1.145 0.062 0.17
Nulliparous 1 0.23 0.226 0.868 0.016 0.69
Age_LMP 1 0.27 0.273 1.046 0.019 0.40
BMI_conception 1 0.18 0.180 0.689 0.012 0.92
HLA.6DRML 2 0.53 0.263 1.007 0.036 0.45
T1Dstatus 1 0.33 0.331 1.269 0.023 0.14
Residuals 46 11.99 0.261 0.831
Total 55 14.42 1.000 [1] 0.136Beta diversity Plot
5.1.3 T1D status in trimester 2
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 4 1.4 0.361 1.354 0.042 0.022 *
Nulliparous 1 0.3 0.324 1.214 0.009 0.188
Age_LMP 1 0.3 0.285 1.070 0.008 0.318
BMI_conception 1 0.3 0.279 1.046 0.008 0.415
HLA.6DRML 2 0.5 0.247 0.928 0.014 0.599
T1Dstatus 1 0.4 0.406 1.522 0.012 0.061 .
Residuals 117 31.2 0.267 0.906
Total 127 34.4 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.061Beta diversity Plot
5.1.4 T1D status in trimester 3
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 5 2.0 0.398 1.55 0.058 0.002 **
Nulliparous 1 0.3 0.277 1.08 0.008 0.321
Age_LMP 1 0.3 0.338 1.31 0.010 0.118
BMI_conception 1 0.3 0.300 1.17 0.009 0.243
HLA.6DRML 2 0.6 0.309 1.21 0.018 0.143
T1Dstatus 1 0.5 0.546 2.12 0.016 0.005 **
Residuals 119 30.6 0.257 0.882
Total 130 34.6 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.005Beta diversity Plot
5.1.5 Days within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.620 2.54 0.020 0.190
seqRun 4 3.1 0.786 3.22 0.052 0.861
Age 1 0.7 0.655 2.69 0.011 0.012 *
Parity 1 0.6 0.562 2.30 0.009 0.645
BMI 1 0.6 0.569 2.33 0.009 0.117
Days 1 0.1 0.126 0.52 0.002 0.497
Residuals 224 54.7 0.244 0.897 0.173
Total 234 61.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
5.1.6 Trimesters within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.620 2.53 0.020 0.200
seqRun 4 3.1 0.786 3.22 0.052 0.839
Age 1 0.7 0.655 2.68 0.011 0.009 **
Parity 1 0.6 0.562 2.30 0.009 0.641
BMI 1 0.6 0.569 2.33 0.009 0.133
Tri 2 0.3 0.141 0.58 0.005 0.708
Residuals 223 54.5 0.244 0.894 0.239
Total 234 61.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Note: The function relevel was used to change the trimester used as reference in the test (e.g. when testing for differences between T2 and T3).
Beta diversity Plot
5.1.7 Days within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.588 2.268 0.036 0.43
seqRun 5 2.0 0.398 1.534 0.061 0.72
Age 1 0.6 0.623 2.405 0.019 0.43
Parity 1 0.5 0.462 1.783 0.014 0.74
BMI 1 0.3 0.275 1.063 0.008 0.63
Days 1 0.2 0.228 0.879 0.007 0.22
Residuals 107 27.7 0.259 0.854 0.57
Total 118 32.5 1.000 Beta diversity Plot
5.1.8 Trimesters within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.588 2.257 0.036 0.43
seqRun 5 2.0 0.398 1.526 0.061 0.72
Age 1 0.6 0.623 2.393 0.019 0.46
Parity 1 0.5 0.462 1.774 0.014 0.74
BMI 1 0.3 0.275 1.057 0.008 0.65
Tri 2 0.3 0.174 0.666 0.011 0.80
Residuals 106 27.6 0.261 0.850 0.71
Total 118 32.5 1.000 Beta diversity Plot
5.1.9 Other factors
5.1.9.1 Age at conception
5.1.9.1.1 Age at conception interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.38 0.013 0.290
T1Dstatus 1 1.0 1.047 4.12 0.011 0.014 *
seqRun 5 3.6 0.729 2.87 0.039 0.744
Tri 2 0.3 0.164 0.65 0.003 0.563
Age 1 0.7 0.739 2.91 0.008 0.387
Parity 1 0.6 0.623 2.45 0.007 0.933
BMI 1 0.5 0.497 1.96 0.005 0.432
Age_Time_Interaction 1 0.2 0.235 0.93 0.002 0.391
Residuals 339 86.2 0.254 0.912 0.120
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.1.2 Age at conception interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.38 0.013 0.28
T1Dstatus 1 1.0 1.047 4.11 0.011 0.01 **
seqRun 5 3.6 0.729 2.86 0.039 0.74
Tri 2 0.3 0.164 0.65 0.003 0.53
Age 1 0.7 0.739 2.90 0.008 0.40
Parity 1 0.6 0.623 2.45 0.007 0.93
BMI 1 0.5 0.497 1.95 0.005 0.46
Age_Time_Interaction 1 0.1 0.104 0.41 0.001 0.93
Residuals 339 86.3 0.255 0.913 0.16
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.1.3 Age at conception interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.38 0.013 0.304
T1Dstatus 1 1.0 1.047 4.11 0.011 0.005 **
seqRun 5 3.6 0.729 2.87 0.039 0.762
Tri 2 0.3 0.164 0.65 0.003 0.542
Age 1 0.7 0.739 2.90 0.008 0.398
Parity 1 0.6 0.623 2.45 0.007 0.936
BMI 1 0.5 0.497 1.95 0.005 0.431
Age_Time_Interaction 1 0.1 0.145 0.57 0.002 0.461
Residuals 339 86.3 0.254 0.913 0.118
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.1.4 Age at conception (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.38 0.013 0.301
T1Dstatus 1 1.0 1.047 4.12 0.011 0.011 *
seqRun 5 3.6 0.729 2.87 0.039 0.745
Tri 2 0.3 0.164 0.65 0.003 0.523
Parity 1 0.6 0.628 2.47 0.007 0.963
BMI 1 0.5 0.501 1.97 0.005 0.559
Age 1 0.7 0.730 2.87 0.008 0.238
Residuals 340 86.4 0.254 0.914 0.111
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.2 Body max index (BMI)
5.1.9.2.1 BMI interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.38 0.013 0.283
T1Dstatus 1 1.0 1.047 4.11 0.011 0.012 *
seqRun 5 3.6 0.729 2.87 0.039 0.735
Tri 2 0.3 0.164 0.65 0.003 0.524
Age 1 0.7 0.739 2.90 0.008 0.421
Parity 1 0.6 0.623 2.45 0.007 0.927
BMI 1 0.5 0.497 1.95 0.005 0.441
BMI_Time_Interaction 1 0.1 0.120 0.47 0.001 0.914
Residuals 339 86.3 0.255 0.913 0.143
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.2.2 BMI interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.38 0.013 0.309
T1Dstatus 1 1.0 1.047 4.11 0.011 0.012 *
seqRun 5 3.6 0.729 2.87 0.039 0.745
Tri 2 0.3 0.164 0.65 0.003 0.562
Age 1 0.7 0.739 2.90 0.008 0.401
Parity 1 0.6 0.623 2.45 0.007 0.925
BMI 1 0.5 0.497 1.95 0.005 0.455
BMI_Time_Interaction 1 0.1 0.140 0.55 0.001 0.740
Residuals 339 86.3 0.255 0.913 0.131
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.2.3 BMI (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.38 0.013 0.314
T1Dstatus 1 1.0 1.047 4.11 0.011 0.008 **
seqRun 5 3.6 0.729 2.87 0.039 0.723
Tri 2 0.3 0.164 0.65 0.003 0.577
Age 1 0.7 0.739 2.90 0.008 0.409
Parity 1 0.6 0.623 2.45 0.007 0.923
BMI 1 0.5 0.497 1.95 0.005 0.452
BMI_Time_Interaction 1 0.2 0.169 0.66 0.002 0.346
Residuals 339 86.2 0.254 0.913 0.105
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.2.4 BMI (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.38 0.013 0.297
T1Dstatus 1 1.0 1.047 4.12 0.011 0.008 **
seqRun 5 3.6 0.729 2.87 0.039 0.750
Tri 2 0.3 0.164 0.65 0.003 0.571
Age 1 0.7 0.739 2.91 0.008 0.406
Parity 1 0.6 0.623 2.45 0.007 0.937
BMI 1 0.5 0.497 1.96 0.005 0.458
Residuals 340 86.4 0.254 0.914 0.102
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.3 HLA type
5.1.9.3.1 HLA type interaction with time (reference: DR34 )
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.38 0.013 0.317
T1Dstatus 1 1.0 1.047 4.12 0.011 0.013 *
Days 1 0.2 0.248 0.98 0.003 0.370
seqRun 5 3.6 0.727 2.86 0.038 0.698
Age 1 0.7 0.735 2.89 0.008 0.401
Parity 1 0.6 0.625 2.46 0.007 0.923
BMI 1 0.5 0.496 1.95 0.005 0.519
HLA_Time_Interaction 1 0.1 0.130 0.51 0.001 1.000
Residuals 340 86.4 0.254 0.914 0.539
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.3.2 HLA type interaction with time (reference: DRXX)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.38 0.013 0.301
T1Dstatus 1 1.0 1.047 4.12 0.011 0.006 **
Days 1 0.2 0.248 0.98 0.003 0.373
seqRun 5 3.6 0.727 2.86 0.038 0.718
Age 1 0.7 0.735 2.89 0.008 0.372
Parity 1 0.6 0.625 2.46 0.007 0.925
BMI 1 0.5 0.496 1.95 0.005 0.507
HLA_Time_Interaction 1 0.1 0.139 0.55 0.001 1.000
Residuals 340 86.4 0.254 0.914 0.330
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.3.3 HLA type interaction with time (reference: Group3o4)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.38 0.013 0.305
T1Dstatus 1 1.0 1.047 4.12 0.011 0.009 **
Days 1 0.2 0.248 0.98 0.003 0.406
seqRun 5 3.6 0.727 2.86 0.038 0.728
Age 1 0.7 0.735 2.89 0.008 0.352
Parity 1 0.6 0.625 2.46 0.007 0.918
BMI 1 0.5 0.496 1.95 0.005 0.500
HLA_Time_Interaction 1 0.2 0.154 0.61 0.002 1.000
Residuals 340 86.4 0.254 0.914 0.243
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.3.4 HLA type (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.3 0.280 1.10 0.003 0.235
seqRun 5 3.7 0.747 2.94 0.040 0.549
Age 1 0.7 0.715 2.82 0.008 0.751
Parity 1 0.7 0.665 2.62 0.007 0.676
BMI 1 0.5 0.499 1.97 0.005 0.247
T1Dstatus 1 1.0 0.984 3.88 0.010 0.018 *
HLA 2 1.1 0.560 2.21 0.012 0.407
Residuals 341 86.5 0.254 0.915 0.089 .
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.4 Parity
5.1.9.4.1 Parity interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.38 0.013 0.29
T1Dstatus 1 1.0 1.047 4.12 0.011 0.01 **
Days 1 0.2 0.248 0.98 0.003 0.35
seqRun 5 3.6 0.727 2.86 0.038 0.72
Age 1 0.7 0.735 2.89 0.008 0.41
Parity 1 0.6 0.625 2.46 0.007 0.92
BMI 1 0.5 0.496 1.95 0.005 0.51
Parity_Time_Interaction 1 0.1 0.105 0.41 0.001 0.91
Residuals 340 86.4 0.254 0.914 0.10 .
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.4.2 Parity (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.39 0.013 0.282
T1Dstatus 1 1.0 1.047 4.13 0.011 0.009 **
Days 1 0.2 0.248 0.98 0.003 0.360
seqRun 5 3.6 0.727 2.87 0.038 0.694
Age 1 0.7 0.735 2.90 0.008 0.365
BMI 1 0.5 0.541 2.13 0.006 0.400
Parity 1 0.6 0.580 2.29 0.006 0.949
Residuals 341 86.5 0.254 0.915 0.084 .
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.5 Mode of delivery
5.1.9.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.42 0.013 0.283
T1Dstatus 1 1.0 1.047 4.18 0.011 0.007 **
MOD 2 1.3 0.650 2.60 0.014 0.187
Days 1 0.2 0.247 0.99 0.003 0.380
seqRun 5 3.7 0.734 2.93 0.039 0.550
Age 1 0.8 0.838 3.35 0.009 0.015 *
Parity 1 0.6 0.625 2.50 0.007 0.863
BMI 1 0.5 0.544 2.18 0.006 0.146
MOD_Time_Interaction 1 0.4 0.423 1.69 0.004 0.979
Residuals 338 84.6 0.250 0.895 0.022 *
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.5.2 Mode of delivery interaction with time (reference: Elective caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.42 0.013 0.28
T1Dstatus 1 1.0 1.047 4.18 0.011 0.01 **
MOD 2 1.3 0.650 2.60 0.014 0.18
Days 1 0.2 0.247 0.99 0.003 0.35
seqRun 5 3.7 0.734 2.93 0.039 0.60
Age 1 0.8 0.838 3.35 0.009 0.01 **
Parity 1 0.6 0.625 2.50 0.007 0.87
BMI 1 0.5 0.544 2.18 0.006 0.11
MOD_Time_Interaction 1 0.5 0.458 1.83 0.005 1.00
Residuals 338 84.6 0.250 0.895 0.16
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.5.3 Mode of delivery interaction with time (reference: Labour)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.605 2.41 0.013 0.301
T1Dstatus 1 1.0 1.047 4.17 0.011 0.006 **
MOD 2 1.3 0.650 2.59 0.014 0.195
Days 1 0.2 0.247 0.99 0.003 0.355
seqRun 5 3.7 0.734 2.92 0.039 0.600
Age 1 0.8 0.838 3.34 0.009 0.014 *
Parity 1 0.6 0.625 2.49 0.007 0.873
BMI 1 0.5 0.544 2.17 0.006 0.126
MOD_Time_Interaction 1 0.2 0.234 0.93 0.002 1.000
Residuals 338 84.8 0.251 0.897 0.320
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.5.4 Mode of delivery (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.3 0.280 1.12 0.003 0.254
seqRun 5 3.7 0.747 2.98 0.040 0.558
Age 1 0.7 0.715 2.85 0.008 0.765
Parity 1 0.7 0.665 2.65 0.007 0.666
BMI 1 0.5 0.499 1.99 0.005 0.262
HLA 2 1.1 0.573 2.29 0.012 0.341
T1Dstatus 1 1.0 0.956 3.81 0.010 0.014 *
MOD 2 1.5 0.742 2.96 0.016 0.054 .
Residuals 339 85.0 0.251 0.900 0.020 *
Total 353 94.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.6 Carbohydrate intake
5.1.9.6.1 Carbohydrate interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.3 0.632 2.510 0.015 0.223
T1Dstatus 1 0.8 0.783 3.111 0.009 0.089 .
Carbs 1 0.5 0.466 1.854 0.005 0.720
seqRun 5 3.5 0.707 2.808 0.041 0.981
Tri 2 0.3 0.153 0.609 0.004 0.414
Age 1 0.7 0.744 2.958 0.009 0.434
Parity 1 0.7 0.662 2.629 0.008 0.811
BMI 1 0.5 0.545 2.167 0.006 0.329
Carb_Time_Interaction 1 0.3 0.272 1.080 0.003 0.186
Residuals 310 78.0 0.252 0.901 0.486
Total 325 86.6 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.6.2 Carbohydrate interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.3 0.632 2.508 0.015 0.241
T1Dstatus 1 0.8 0.783 3.107 0.009 0.082 .
Carbs 1 0.5 0.466 1.852 0.005 0.736
seqRun 5 3.5 0.707 2.806 0.041 0.964
Tri 2 0.3 0.153 0.609 0.004 0.404
Age 1 0.7 0.744 2.955 0.009 0.431
Parity 1 0.7 0.662 2.626 0.008 0.809
BMI 1 0.5 0.545 2.165 0.006 0.345
Carb_Time_Interaction 1 0.2 0.195 0.774 0.002 0.757
Residuals 310 78.1 0.252 0.902 0.581
Total 325 86.6 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.6.3 Carbohydrate interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.3 0.632 2.505 0.015 0.26
T1Dstatus 1 0.8 0.783 3.104 0.009 0.10
Carbs 1 0.5 0.466 1.850 0.005 0.74
seqRun 5 3.5 0.707 2.803 0.041 0.97
Tri 2 0.3 0.153 0.608 0.004 0.41
Age 1 0.7 0.744 2.952 0.009 0.44
Parity 1 0.7 0.662 2.624 0.008 0.81
BMI 1 0.5 0.545 2.162 0.006 0.35
Carb_Time_Interaction 1 0.1 0.115 0.457 0.001 1.00
Residuals 310 78.2 0.252 0.903 0.66
Total 325 86.6 1.000 5.1.9.6.4 Carbohydrate (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 5 3.8 0.751 2.982 0.043 0.716
Tri 2 0.3 0.154 0.611 0.004 0.415
Age 1 0.7 0.741 2.945 0.009 0.628
Parity 1 0.7 0.686 2.726 0.008 0.830
BMI 1 0.5 0.535 2.126 0.006 0.192
HLA 2 1.2 0.584 2.319 0.013 0.317
T1Dstatus 1 0.8 0.761 3.023 0.009 0.079 .
Carbs 1 0.4 0.352 1.400 0.004 0.939
Residuals 311 78.3 0.252 0.904 0.524
Total 325 86.6 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.7 Fibre intake
5.1.9.7.1 Fibre interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.3 0.632 2.515 0.015 0.255
T1Dstatus 1 0.8 0.783 3.116 0.009 0.086 .
Fiber 1 0.6 0.624 2.482 0.007 0.284
seqRun 5 3.6 0.717 2.854 0.041 0.938
Tri 2 0.3 0.152 0.607 0.004 0.425
Age 1 0.7 0.742 2.956 0.009 0.455
Parity 1 0.7 0.653 2.601 0.008 0.865
BMI 1 0.5 0.531 2.112 0.006 0.462
Fiber_Time_Interaction 1 0.2 0.230 0.916 0.003 0.093 .
Residuals 310 77.9 0.251 0.899 0.289
Total 325 86.6 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.7.2 Fibre interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.3 0.632 2.514 0.015 0.261
T1Dstatus 1 0.8 0.783 3.114 0.009 0.092 .
Fiber 1 0.6 0.624 2.481 0.007 0.276
seqRun 5 3.6 0.717 2.852 0.041 0.938
Tri 2 0.3 0.152 0.607 0.004 0.445
Age 1 0.7 0.742 2.954 0.009 0.438
Parity 1 0.7 0.653 2.599 0.008 0.854
BMI 1 0.5 0.531 2.111 0.006 0.481
Fiber_Time_Interaction 1 0.2 0.188 0.750 0.002 0.994
Residuals 310 77.9 0.251 0.900 0.485
Total 325 86.6 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.7.3 Fibre interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.3 0.632 2.513 0.015 0.21
T1Dstatus 1 0.8 0.783 3.113 0.009 0.10
Fiber 1 0.6 0.624 2.480 0.007 0.29
seqRun 5 3.6 0.717 2.851 0.041 0.93
Tri 2 0.3 0.152 0.606 0.004 0.41
Age 1 0.7 0.742 2.953 0.009 0.48
Parity 1 0.7 0.653 2.598 0.008 0.86
BMI 1 0.5 0.531 2.110 0.006 0.48
Fiber_Time_Interaction 1 0.2 0.161 0.639 0.002 1.00
Residuals 310 77.9 0.251 0.900 0.50
Total 325 86.6 1.000 5.1.9.7.4 Fibre (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 5 3.8 0.751 2.989 0.043 0.710
Tri 2 0.3 0.154 0.612 0.004 0.432
Age 1 0.7 0.741 2.952 0.009 0.644
Parity 1 0.7 0.686 2.733 0.008 0.803
BMI 1 0.5 0.535 2.131 0.006 0.190
HLA 2 1.2 0.584 2.324 0.013 0.312
T1Dstatus 1 0.8 0.761 3.030 0.009 0.091 .
Fiber 1 0.5 0.534 2.127 0.006 0.444
Residuals 311 78.1 0.251 0.902 0.337
Total 325 86.6 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.8 1,5-AG (glucose control measurement)
5.1.9.8.1 1,5-AG interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.598 2.38 0.014 0.300
T1Dstatus 1 1.2 1.163 4.62 0.013 0.005 **
Days 1 0.2 0.246 0.98 0.003 0.233
seqRun 4 3.2 0.794 3.16 0.036 0.772
Age 1 0.8 0.800 3.18 0.009 0.233
Parity 1 0.6 0.580 2.31 0.007 0.894
BMI 1 0.4 0.446 1.77 0.005 0.282
AG15 1 0.8 0.832 3.31 0.010 0.006 **
AG15_T1D_Interaction 1 0.4 0.374 1.49 0.004 1.000
Residuals 311 78.2 0.252 0.899 0.067 .
Total 324 87.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.8.2 1,5-AG within T1D women
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.597 2.448 0.021 0.19
Days 1 0.2 0.168 0.689 0.003 0.43
seqRun 4 2.9 0.718 2.946 0.052 0.95
Age 1 0.6 0.624 2.560 0.011 0.01 **
Parity 1 0.5 0.516 2.117 0.009 0.57
BMI 1 0.5 0.540 2.214 0.010 0.12
AG15 1 0.5 0.451 1.850 0.008 0.27
Residuals 202 49.2 0.244 0.886 0.21
Total 213 55.6 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.8.3 1,5-AG interaction with time (within non-T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.18 0.592 2.35 0.039 0.43
Days 1 0.26 0.260 1.03 0.009 0.22
seqRun 3 1.47 0.491 1.95 0.049 0.72
Age 1 0.67 0.668 2.65 0.022 0.63
Parity 1 0.49 0.487 1.93 0.016 0.53
BMI 1 0.26 0.255 1.01 0.008 0.86
AG15 1 0.74 0.741 2.94 0.024 0.26
Residuals 100 25.22 0.252 0.833 0.45
Total 110 30.29 1.000 5.1.9.8.4 1,5-AG (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.598 2.37 0.014 0.272
T1Dstatus 1 1.2 1.163 4.62 0.013 0.002 **
Days 1 0.2 0.246 0.97 0.003 0.212
seqRun 4 3.2 0.794 3.15 0.036 0.736
Age 1 0.8 0.800 3.17 0.009 0.260
Parity 1 0.6 0.580 2.30 0.007 0.899
BMI 1 0.4 0.446 1.77 0.005 0.296
AG15 1 0.8 0.832 3.30 0.010 0.004 **
Residuals 312 78.6 0.252 0.903 0.006 **
Total 324 87.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.1.9.9 Pre-eclampsia (within T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 1.2 0.620 2.55 0.020 0.196
Days 1 0.2 0.162 0.66 0.003 0.485
seqRun 4 3.1 0.778 3.20 0.051 0.879
Age 1 0.6 0.644 2.65 0.011 0.016 *
Parity 1 0.6 0.566 2.33 0.009 0.608
BMI 1 0.6 0.574 2.36 0.009 0.089 .
Preeclampsia 1 0.4 0.432 1.77 0.007 0.173
Residuals 223 54.2 0.243 0.890 0.159
Total 234 61.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 15.2 Differential abundance analysis Species taxonomic level
Differential abundance analysis with limma using voom pipeline with structural zeros - Gordon
Improved analysis using TMM normalization and voom with structural zeros.
A linear model is fit to the data and differential abundance is assessed using empirical bayes. The false discovery rate (FDR) for this analysis is set at 5%. For a OTU to be classified as differentially abundant (DA), its change in abundance between the groups (T1D vs nonT1D) must be significant. In the results tables to follow, the genes that are DE are those that have an adjusted p-value less than the FDR. Note that adjusted p-value is used opposed to the initial p-value as it has been adjusted for multiple testing. Therefore any adjusted p-value less than 0.05 is deemed statistically significant, identifying the associated gene as DA.
Those genes that are DA are then determined to be more- or less abundant depending on the direction of their log-fold change. Those OTUs with a positive log-fold change are more abundant, while those OTUs with a negative log-fold change are less abundant.
Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type
nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down 0 0 0 1 0 1 5 0 0 0
NotSig 336 347 338 330 349 348 343 349 349 349
Up 13 2 11 18 0 0 1 0 0 0
noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down 0 0 4
NotSig 349 349 344
Up 0 0 1Differentially abundant species were found between T1D and non-T1D women across pregnancy and within each trimester. No differentially abundant species were detected between trimesters in samples form T1D and non-T1D women together or separatelly.
Results for contrasts with significant differentially abundant species are shown below
Only those taxa with prevalence > 50% and LogFC > 0.5 of < -0.5 are considered as biologically relevant in our analyses.
5.2.1 Across all trimesters (T1D vs non-T1D)
Classification LogFC P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
1 Bacteroides -1.54 0.00319 0.0695 0.507 58 1.65 70.2
Feature
1 4d7b30ba940df2f77a91e77e2836842cFrom 11 OTUs that limma identified as differentially abundant, only one (further classified as Bacteroides caccae in blast), had >50% prevalence in either of the groups (i.e. T1D or non-T1D). Here, we will just show hoe to plot mean and standard error of this differentially abundant taxa, however, this code can be used to plot any taxa that was differentially abundant in the rest of the analysis.
5.2.2 Only Trimester 1 (nonT1D vs T1D)
[1] Classification LogFC P.Val adj.P.Val nonT1D:mean%
[6] Prev% T1D:mean% T1D:Prev%
<0 rows> (or 0-length row.names)5.2.3 Only Trimester 2 (nonT1D vs T1D)
Classification LogFC P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
1 Lachnospiraceae 1.46 0.00273 0.0734 0.311 70.5 0.153 445.2.4 Only Trimester 3 (nonT1D vs T1D)
Classification LogFC P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
1 Bacteroides -1.97 0.000658 0.0164 0.419 58.7 2.08 77.65.2.5 T1 vs T2 (T1D and non-T1D data)
[1] Classification LogFC P.Val adj.P.Val T1:mean%
[6] T1Prev% T2:mean% T2Prev% T3:mean% T3Prev%
<0 rows> (or 0-length row.names)5.2.6 T2 vs T3 (T1D and non-T1D data)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Oscillibacter -0.579 9.68e-05 0.0338 0.064 53.6
2 Oscillibacter -0.579 9.68e-05 0.0338 0.050 43.0
3 Oscillibacter -0.579 9.68e-05 0.0338 0.085 55.75.2.7 T1 vs T3 (T1D and non-T1D data)
Classification LogFC P.Val adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev%
1 Erysipelotrichaceae -0.753 0.002511 0.0674 0.133 66.1 0.18 72.8
2 Streptococcus -0.998 0.000107 0.0125 0.149 51.8 0.25 57.6
3 Oscillibacter -0.734 0.000512 0.0298 0.064 53.6 0.05 43.0
T3:mean% T3Prev%
1 0.229 82.1
2 0.326 71.4
3 0.085 55.75.2.8 T1 vs T2 (in women with T1D)
Classification LogFC P.Val adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev%
1 Lachnospiraceae -1.09 0.000426 0.0744 0.057 31.6 0.206 54.25.2.9 T2 vs T3 (in women with T1D)
[1] "No DA taxa"5.2.10 T1 vs T3 (in women with T1D)
[1] "No DA taxa"5.2.11 T1 vs T2 (in women without T1D)
[1] "No DA taxa"5.2.12 T2 vs T3 (in women without T1D)
[1] "No DA taxa"5.2.13 T1 vs T3 (in women without T1D)
Classification LogFC P.Val adj.P.Val T1:mean% T1Prev% T3:mean% T3Prev%
1 Oscillibacter -1.37 8.07e-05 0.00939 0.024 38.9 0.11 626 Genus taxonomic level
6.1 Microbial community composition analysis at Genus level (Beta diversity analysis)
6.1.1 Interaction between T1D status and Time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 5 1.9 0.389 2.90 0.039 0.548
Days 1 0.2 0.233 1.74 0.005 0.085 .
T1D_Time_Interaction 1 1.0 1.032 7.69 0.021 0.051 .
Age 1 0.4 0.356 2.65 0.007 0.826
Parity 1 0.3 0.335 2.49 0.007 0.497
BMI 1 0.1 0.089 0.67 0.002 0.873
HLA 2 0.5 0.237 1.77 0.009 0.599
T1Dstatus 1 0.1 0.096 0.72 0.002 0.964
Residuals 340 45.6 0.134 0.909 0.757
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.0516.1.2 T1D status in trimester 1
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.36 0.1184 0.802 0.044 0.72
Nulliparous 1 0.12 0.1167 0.791 0.015 0.59
Age_LMP 1 0.22 0.2165 1.467 0.027 0.15
BMI_conception 1 0.06 0.0632 0.428 0.008 0.90
HLA.6DRML 2 0.26 0.1307 0.885 0.033 0.56
T1Dstatus 1 0.18 0.1777 1.203 0.022 0.27
Residuals 46 6.79 0.1477 0.851
Total 55 7.98 1.000 [1] 0.274Beta diversity Plot
6.1.3 T1D status in trimester 2
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 4 0.74 0.184 1.34 0.041 0.165
Nulliparous 1 0.20 0.205 1.48 0.011 0.153
Age_LMP 1 0.19 0.191 1.39 0.011 0.213
BMI_conception 1 0.07 0.066 0.48 0.004 0.877
HLA.6DRML 2 0.20 0.099 0.72 0.011 0.756
T1Dstatus 1 0.49 0.487 3.53 0.027 0.004 **
Residuals 117 16.13 0.138 0.895
Total 127 18.01 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.004Beta diversity Plot
6.1.4 T1D status in trimester 3
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 5 0.90 0.180 1.32 0.049 0.164
Nulliparous 1 0.22 0.220 1.62 0.012 0.113
Age_LMP 1 0.17 0.173 1.28 0.010 0.241
BMI_conception 1 0.10 0.100 0.74 0.006 0.600
HLA.6DRML 2 0.16 0.078 0.57 0.009 0.875
T1Dstatus 1 0.47 0.470 3.46 0.026 0.005 **
Residuals 119 16.19 0.136 0.889
Total 130 18.20 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.005Beta diversity Plot
6.1.5 Days within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.68 0.338 2.95 0.023 0.19
seqRun 4 1.92 0.481 4.20 0.066 0.81
Age 1 0.29 0.290 2.54 0.010 0.31
Parity 1 0.24 0.241 2.11 0.008 0.72
BMI 1 0.24 0.236 2.06 0.008 0.20
Days 1 0.12 0.117 1.02 0.004 0.12
Residuals 224 25.65 0.115 0.880 0.27
Total 234 29.14 1.000 Beta diversity Plot
6.1.6 Trimester within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.68 0.338 2.94 0.023 0.17
seqRun 4 1.92 0.481 4.19 0.066 0.80
Age 1 0.29 0.290 2.53 0.010 0.28
Parity 1 0.24 0.241 2.10 0.008 0.73
BMI 1 0.24 0.236 2.06 0.008 0.18
Tri 2 0.15 0.076 0.66 0.005 0.35
Residuals 223 25.62 0.115 0.879 0.31
Total 234 29.14 1.000 Beta diversity Plot
6.1.7 Days within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.67 0.333 2.03 0.033 0.490
seqRun 5 0.72 0.144 0.88 0.036 0.946
Age 1 0.55 0.550 3.36 0.027 0.308
Parity 1 0.38 0.384 2.34 0.019 0.058 .
BMI 1 0.12 0.124 0.76 0.006 0.596
Days 1 0.17 0.165 1.01 0.008 0.121
Residuals 107 17.51 0.164 0.870 0.661
Total 118 20.12 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
6.1.8 Trimester within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.67 0.333 2.01 0.033 0.490
seqRun 5 0.72 0.144 0.87 0.036 0.955
Age 1 0.55 0.550 3.32 0.027 0.274
Parity 1 0.38 0.384 2.32 0.019 0.082 .
BMI 1 0.12 0.124 0.75 0.006 0.590
Tri 2 0.14 0.068 0.41 0.007 0.852
Residuals 106 17.54 0.165 0.872 0.808
Total 118 20.12 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
6.1.9 Other factors
6.1.9.1 Age at conception
6.1.9.1.1 Age at conception interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.61 0.009 0.705
T1Dstatus 1 1.1 1.106 8.22 0.022 0.005 **
seqRun 5 1.9 0.383 2.85 0.038 0.649
Tri 2 0.2 0.085 0.64 0.003 0.515
Age 1 0.4 0.410 3.05 0.008 0.903
Parity 1 0.3 0.309 2.30 0.006 0.974
BMI 1 0.1 0.103 0.77 0.002 0.820
Age_Time_Interaction 1 0.1 0.143 1.06 0.003 0.681
Residuals 339 45.6 0.134 0.909 0.294
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.1.2 Age at conception interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.60 0.009 0.733
T1Dstatus 1 1.1 1.106 8.21 0.022 0.005 **
seqRun 5 1.9 0.383 2.84 0.038 0.654
Tri 2 0.2 0.085 0.63 0.003 0.525
Age 1 0.4 0.410 3.04 0.008 0.882
Parity 1 0.3 0.309 2.29 0.006 0.974
BMI 1 0.1 0.103 0.77 0.002 0.830
Age_Time_Interaction 1 0.0 0.043 0.32 0.001 0.854
Residuals 339 45.7 0.135 0.911 0.303
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.1.3 Age at conception interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.61 0.009 0.742
T1Dstatus 1 1.1 1.106 8.21 0.022 0.005 **
seqRun 5 1.9 0.383 2.84 0.038 0.633
Tri 2 0.2 0.085 0.63 0.003 0.515
Age 1 0.4 0.410 3.04 0.008 0.886
Parity 1 0.3 0.309 2.29 0.006 0.974
BMI 1 0.1 0.103 0.77 0.002 0.841
Age_Time_Interaction 1 0.1 0.060 0.44 0.001 0.553
Residuals 339 45.7 0.135 0.910 0.249
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.1.4 Age at conception (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.61 0.009 0.718
T1Dstatus 1 1.1 1.106 8.22 0.022 0.007 **
seqRun 5 1.9 0.383 2.85 0.038 0.645
Tri 2 0.2 0.085 0.64 0.003 0.520
Parity 1 0.3 0.303 2.25 0.006 0.994
BMI 1 0.1 0.103 0.76 0.002 0.865
Age 1 0.4 0.416 3.09 0.008 0.746
Residuals 340 45.7 0.135 0.911 0.241
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.2 Body max index (BMI)
6.1.9.2.1 BMI interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.60 0.009 0.738
T1Dstatus 1 1.1 1.106 8.20 0.022 0.002 **
seqRun 5 1.9 0.383 2.84 0.038 0.652
Tri 2 0.2 0.085 0.63 0.003 0.526
Age 1 0.4 0.410 3.04 0.008 0.902
Parity 1 0.3 0.309 2.29 0.006 0.974
BMI 1 0.1 0.103 0.77 0.002 0.826
BMI_Time_Interaction 1 0.0 0.019 0.14 0.000 0.987
Residuals 339 45.7 0.135 0.911 0.338
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.2.2 BMI interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.60 0.009 0.743
T1Dstatus 1 1.1 1.106 8.20 0.022 0.004 **
seqRun 5 1.9 0.383 2.84 0.038 0.645
Tri 2 0.2 0.085 0.63 0.003 0.482
Age 1 0.4 0.410 3.04 0.008 0.897
Parity 1 0.3 0.309 2.29 0.006 0.969
BMI 1 0.1 0.103 0.77 0.002 0.814
BMI_Time_Interaction 1 0.0 0.023 0.17 0.000 0.974
Residuals 339 45.7 0.135 0.911 0.336
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.2.3 BMI (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.60 0.009 0.739
T1Dstatus 1 1.1 1.106 8.21 0.022 0.007 **
seqRun 5 1.9 0.383 2.84 0.038 0.637
Tri 2 0.2 0.085 0.63 0.003 0.536
Age 1 0.4 0.410 3.04 0.008 0.887
Parity 1 0.3 0.309 2.29 0.006 0.972
BMI 1 0.1 0.103 0.77 0.002 0.797
BMI_Time_Interaction 1 0.0 0.047 0.35 0.001 0.822
Residuals 339 45.7 0.135 0.910 0.312
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.2.4 BMI (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.61 0.009 0.716
T1Dstatus 1 1.1 1.106 8.22 0.022 0.004 **
seqRun 5 1.9 0.383 2.85 0.038 0.614
Tri 2 0.2 0.085 0.64 0.003 0.577
Age 1 0.4 0.410 3.05 0.008 0.881
Parity 1 0.3 0.309 2.30 0.006 0.975
BMI 1 0.1 0.103 0.77 0.002 0.802
Residuals 340 45.7 0.135 0.911 0.259
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.3 HLA type
6.1.9.3.1 HLA type interaction with time (reference: DR34 )
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.61 0.009 0.726
T1Dstatus 1 1.1 1.106 8.25 0.022 0.002 **
Days 1 0.3 0.258 1.92 0.005 0.161
seqRun 5 1.9 0.376 2.80 0.037 0.647
Age 1 0.4 0.387 2.88 0.008 0.905
Parity 1 0.3 0.304 2.26 0.006 0.978
BMI 1 0.1 0.101 0.76 0.002 0.826
HLA_Time_Interaction 1 0.1 0.106 0.79 0.002 0.996
Residuals 340 45.6 0.134 0.909 0.233
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.3.2 HLA type interaction with time (reference: DRXX)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.61 0.009 0.719
T1Dstatus 1 1.1 1.106 8.24 0.022 0.002 **
Days 1 0.3 0.258 1.92 0.005 0.160
seqRun 5 1.9 0.376 2.80 0.037 0.629
Age 1 0.4 0.387 2.88 0.008 0.906
Parity 1 0.3 0.304 2.26 0.006 0.975
BMI 1 0.1 0.101 0.76 0.002 0.822
HLA_Time_Interaction 1 0.1 0.052 0.39 0.001 1.000
Residuals 340 45.7 0.134 0.910 0.287
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.3.3 HLA type interaction with time (reference: Group3o4)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.61 0.009 0.723
T1Dstatus 1 1.1 1.106 8.24 0.022 0.004 **
Days 1 0.3 0.258 1.92 0.005 0.171
seqRun 5 1.9 0.376 2.80 0.037 0.652
Age 1 0.4 0.387 2.88 0.008 0.902
Parity 1 0.3 0.304 2.26 0.006 0.969
BMI 1 0.1 0.101 0.76 0.002 0.814
HLA_Time_Interaction 1 0.1 0.064 0.48 0.001 0.996
Residuals 340 45.6 0.134 0.910 0.248
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.3.4 HLA type (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.3 0.276 2.06 0.006 0.126
seqRun 5 1.9 0.381 2.84 0.038 0.591
Age 1 0.5 0.450 3.36 0.009 0.631
Parity 1 0.4 0.383 2.86 0.008 0.174
BMI 1 0.1 0.113 0.84 0.002 0.663
T1Dstatus 1 0.9 0.853 6.37 0.017 0.016 *
HLA 2 0.5 0.245 1.83 0.010 0.567
Residuals 341 45.7 0.134 0.911 0.175
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.4 Parity
6.1.9.4.1 Parity interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.61 0.009 0.713
T1Dstatus 1 1.1 1.106 8.24 0.022 0.002 **
Days 1 0.3 0.258 1.92 0.005 0.172
seqRun 5 1.9 0.376 2.80 0.037 0.646
Age 1 0.4 0.387 2.88 0.008 0.881
Parity 1 0.3 0.304 2.26 0.006 0.971
BMI 1 0.1 0.101 0.76 0.002 0.835
Parity_Time_Interaction 1 0.1 0.075 0.56 0.001 0.494
Residuals 340 45.6 0.134 0.909 0.197
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.4.2 Parity (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.61 0.009 0.691
T1Dstatus 1 1.1 1.106 8.25 0.022 0.004 **
Days 1 0.3 0.258 1.92 0.005 0.180
seqRun 5 1.9 0.376 2.81 0.037 0.656
Age 1 0.4 0.387 2.89 0.008 0.894
BMI 1 0.1 0.120 0.89 0.002 0.535
Parity 1 0.3 0.285 2.13 0.006 0.989
Residuals 341 45.7 0.134 0.911 0.179
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.5 Mode of delivery
6.1.9.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.64 0.009 0.759
T1Dstatus 1 1.1 1.106 8.37 0.022 0.002 **
MOD 2 0.8 0.413 3.13 0.016 0.137
Days 1 0.3 0.251 1.90 0.005 0.174
seqRun 5 1.9 0.384 2.91 0.038 0.592
Age 1 0.5 0.535 4.05 0.011 0.117
Parity 1 0.3 0.317 2.40 0.006 0.883
BMI 1 0.1 0.071 0.54 0.001 0.987
MOD_Time_Interaction 1 0.1 0.073 0.55 0.001 1.000
Residuals 338 44.6 0.132 0.890 0.088 .
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.5.2 Mode of delivery interaction with time (reference: Elective caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.64 0.009 0.721
T1Dstatus 1 1.1 1.106 8.39 0.022 0.003 **
MOD 2 0.8 0.413 3.13 0.016 0.141
Days 1 0.3 0.251 1.90 0.005 0.184
seqRun 5 1.9 0.384 2.92 0.038 0.586
Age 1 0.5 0.535 4.06 0.011 0.105
Parity 1 0.3 0.317 2.41 0.006 0.882
BMI 1 0.1 0.071 0.54 0.001 0.991
MOD_Time_Interaction 1 0.2 0.188 1.42 0.004 1.000
Residuals 338 44.5 0.132 0.887 0.447
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.5.3 Mode of delivery interaction with time (reference: Labour)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.216 1.64 0.009 0.732
T1Dstatus 1 1.1 1.106 8.38 0.022 0.003 **
MOD 2 0.8 0.413 3.13 0.016 0.162
Days 1 0.3 0.251 1.90 0.005 0.179
seqRun 5 1.9 0.384 2.91 0.038 0.613
Age 1 0.5 0.535 4.05 0.011 0.111
Parity 1 0.3 0.317 2.40 0.006 0.897
BMI 1 0.1 0.071 0.54 0.001 0.990
MOD_Time_Interaction 1 0.1 0.108 0.82 0.002 1.000
Residuals 338 44.6 0.132 0.889 0.395
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.5.4 Mode of delivery (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.3 0.276 2.09 0.006 0.146
seqRun 5 1.9 0.381 2.88 0.038 0.584
Age 1 0.5 0.450 3.41 0.009 0.609
Parity 1 0.4 0.383 2.90 0.008 0.198
BMI 1 0.1 0.113 0.85 0.002 0.677
HLA 2 0.4 0.184 1.39 0.007 0.838
T1Dstatus 1 1.0 0.977 7.40 0.019 0.006 **
MOD 2 1.0 0.496 3.76 0.020 0.061 .
Residuals 339 44.7 0.132 0.891 0.062 .
Total 353 50.2 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.6 Carbohydrate intake
6.1.9.6.1 Carbohydrate interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.5 0.254 1.96 0.011 0.576
T1Dstatus 1 0.7 0.660 5.09 0.015 0.037 *
Carbs 1 0.2 0.204 1.57 0.005 0.689
seqRun 5 2.2 0.431 3.32 0.048 0.714
Tri 2 0.2 0.075 0.58 0.003 0.499
Age 1 0.4 0.414 3.19 0.009 0.811
Parity 1 0.3 0.325 2.51 0.007 0.946
BMI 1 0.1 0.128 0.98 0.003 0.715
Carb_Time_Interaction 1 0.3 0.260 2.00 0.006 0.002 **
Residuals 310 40.2 0.130 0.893 0.553
Total 325 45.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.6.2 Carbohydrate interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.5 0.254 1.96 0.011 0.562
T1Dstatus 1 0.7 0.660 5.08 0.015 0.041 *
Carbs 1 0.2 0.204 1.57 0.005 0.650
seqRun 5 2.2 0.431 3.31 0.048 0.695
Tri 2 0.2 0.075 0.58 0.003 0.484
Age 1 0.4 0.414 3.18 0.009 0.813
Parity 1 0.3 0.325 2.50 0.007 0.949
BMI 1 0.1 0.128 0.98 0.003 0.744
Carb_Time_Interaction 1 0.2 0.152 1.17 0.003 0.083 .
Residuals 310 40.3 0.130 0.896 0.604
Total 325 45.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.6.3 Carbohydrate interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.5 0.254 1.95 0.011 0.584
T1Dstatus 1 0.7 0.660 5.08 0.015 0.049 *
Carbs 1 0.2 0.204 1.56 0.005 0.678
seqRun 5 2.2 0.431 3.31 0.048 0.699
Tri 2 0.2 0.075 0.58 0.003 0.495
Age 1 0.4 0.414 3.18 0.009 0.826
Parity 1 0.3 0.325 2.50 0.007 0.952
BMI 1 0.1 0.128 0.98 0.003 0.765
Carb_Time_Interaction 1 0.1 0.128 0.98 0.003 0.048 *
Residuals 310 40.3 0.130 0.896 0.615
Total 325 45.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.6.4 Carbohydrate (no interaction within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.45 0.150 1.092 0.065 0.001 ***
Age 1 0.34 0.336 2.446 0.048 0.001 ***
Parity 1 0.09 0.094 0.686 0.014 0.001 ***
BMI 1 0.09 0.094 0.685 0.014 0.001 ***
HLA 2 0.27 0.134 0.979 0.039 0.440
T1Dstatus 1 0.17 0.171 1.243 0.025 0.263
Carbs 1 0.17 0.166 1.208 0.024 0.292
Residuals 39 5.35 0.137 0.772 0.331
Total 49 6.93 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.6.5 Carbohydrate (no interaction within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 1.20 0.300 2.325 0.062 0.30
Age 1 0.22 0.217 1.683 0.011 0.90
Parity 1 0.22 0.218 1.690 0.011 0.71
BMI 1 0.04 0.038 0.294 0.002 0.76
HLA 2 0.24 0.118 0.914 0.012 0.80
T1Dstatus 1 0.27 0.271 2.097 0.014 0.12
Carbs 1 0.13 0.131 1.015 0.007 0.57
Residuals 132 17.06 0.129 0.881 0.53
Total 143 19.38 1.000 6.1.9.6.6 Carbohydrate (no interaction within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 0.95 0.2373 1.727 0.051 0.776
Age 1 0.15 0.1497 1.089 0.008 0.184
Parity 1 0.25 0.2508 1.825 0.014 0.614
BMI 1 0.09 0.0945 0.687 0.005 0.140
HLA 2 0.17 0.0869 0.633 0.009 0.915
T1Dstatus 1 0.30 0.3024 2.200 0.016 0.097 .
Carbs 1 0.14 0.1418 1.032 0.008 0.473
Residuals 120 16.49 0.1374 0.889 0.747
Total 131 18.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.7 Fibre intake
6.1.9.7.1 Fibre interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.5 0.254 1.97 0.011 0.564
T1Dstatus 1 0.7 0.660 5.12 0.015 0.046 *
Fiber 1 0.3 0.297 2.30 0.007 0.365
seqRun 5 2.3 0.458 3.55 0.051 0.553
Tri 2 0.1 0.072 0.56 0.003 0.535
Age 1 0.4 0.410 3.18 0.009 0.801
Parity 1 0.3 0.308 2.39 0.007 0.983
BMI 1 0.1 0.119 0.92 0.003 0.839
Fiber_Time_Interaction 1 0.3 0.272 2.11 0.006 0.001 ***
Residuals 310 40.0 0.129 0.889 0.306
Total 325 45.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.7.2 Fibre interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.5 0.254 1.96 0.011 0.601
T1Dstatus 1 0.7 0.660 5.10 0.015 0.036 *
Fiber 1 0.3 0.297 2.29 0.007 0.379
seqRun 5 2.3 0.458 3.53 0.051 0.569
Tri 2 0.1 0.072 0.56 0.003 0.506
Age 1 0.4 0.410 3.16 0.009 0.823
Parity 1 0.3 0.308 2.38 0.007 0.976
BMI 1 0.1 0.119 0.92 0.003 0.827
Fiber_Time_Interaction 1 0.1 0.105 0.81 0.002 0.765
Residuals 310 40.2 0.130 0.892 0.532
Total 325 45.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.7.3 Fibre interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.5 0.254 1.97 0.011 0.589
T1Dstatus 1 0.7 0.660 5.11 0.015 0.039 *
Fiber 1 0.3 0.297 2.30 0.007 0.386
seqRun 5 2.3 0.458 3.54 0.051 0.560
Tri 2 0.1 0.072 0.56 0.003 0.524
Age 1 0.4 0.410 3.17 0.009 0.825
Parity 1 0.3 0.308 2.39 0.007 0.978
BMI 1 0.1 0.119 0.92 0.003 0.834
Fiber_Time_Interaction 1 0.2 0.202 1.56 0.004 0.606
Residuals 310 40.1 0.129 0.890 0.540
Total 325 45.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.7.4 Fibre (no interaction within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.45 0.150 1.077 0.065 0.001 ***
Age 1 0.34 0.336 2.414 0.048 0.001 ***
Parity 1 0.09 0.094 0.677 0.014 0.001 ***
BMI 1 0.09 0.094 0.676 0.014 0.001 ***
HLA 2 0.27 0.134 0.966 0.039 0.435
T1Dstatus 1 0.17 0.171 1.227 0.025 0.266
Fiber 1 0.09 0.094 0.673 0.014 0.658
Residuals 39 5.43 0.139 0.783 0.514
Total 49 6.93 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.7.5 Fibre (no interaction within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 1.20 0.300 2.324 0.062 0.31
Age 1 0.22 0.217 1.683 0.011 0.88
Parity 1 0.22 0.218 1.690 0.011 0.69
BMI 1 0.04 0.038 0.294 0.002 0.75
HLA 2 0.24 0.118 0.914 0.012 0.78
T1Dstatus 1 0.27 0.271 2.097 0.014 0.13
Fiber 1 0.13 0.128 0.989 0.007 0.59
Residuals 132 17.06 0.129 0.881 0.57
Total 143 19.38 1.000 6.1.9.7.6 Fibre (no interaction within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 0.95 0.237 1.76 0.051 0.775
Age 1 0.15 0.150 1.11 0.008 0.145
Parity 1 0.25 0.251 1.86 0.014 0.647
BMI 1 0.09 0.094 0.70 0.005 0.118
HLA 2 0.17 0.087 0.65 0.009 0.913
T1Dstatus 1 0.30 0.302 2.24 0.016 0.085 .
Fiber 1 0.47 0.467 3.47 0.025 0.019 *
Residuals 120 16.17 0.135 0.871 0.553
Total 131 18.55 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.8 1,5-AG (glucose control measurement)
6.1.9.8.1 1,5-AG interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.5 0.235 1.78 0.010 0.644
T1Dstatus 1 1.3 1.253 9.49 0.027 0.003 **
Days 1 0.3 0.259 1.96 0.006 0.069 .
seqRun 4 1.8 0.444 3.36 0.038 0.214
Age 1 0.5 0.518 3.92 0.011 0.854
Parity 1 0.3 0.259 1.96 0.006 0.995
BMI 1 0.1 0.110 0.84 0.002 0.153
AG15 1 0.5 0.501 3.79 0.011 0.086 .
AG15_T1D_Interaction 1 0.2 0.221 1.67 0.005 1.000
Residuals 311 41.1 0.132 0.884 0.041 *
Total 324 46.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.8.2 1,5-AG within T1D women
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.75 0.375 3.31 0.029 0.083 .
Days 1 0.17 0.171 1.51 0.007 0.069 .
seqRun 4 1.60 0.400 3.53 0.061 0.943
Age 1 0.27 0.270 2.38 0.010 0.382
Parity 1 0.19 0.185 1.63 0.007 0.627
BMI 1 0.21 0.207 1.82 0.008 0.125
AG15 1 0.19 0.194 1.71 0.007 0.848
Residuals 202 22.91 0.113 0.871 0.232
Total 213 26.28 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.8.3 1,5-AG interaction with time (within non-T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.71 0.355 2.23 0.037 0.48
Days 1 0.21 0.212 1.33 0.011 0.15
seqRun 3 0.57 0.189 1.19 0.030 0.83
Age 1 0.65 0.648 4.07 0.034 0.45
Parity 1 0.39 0.387 2.43 0.020 0.11
BMI 1 0.12 0.123 0.77 0.006 0.78
AG15 1 0.56 0.560 3.52 0.029 0.10
Residuals 100 15.92 0.159 0.832 0.31
Total 110 19.13 1.000 6.1.9.8.4 1,5-AG (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.5 0.235 1.77 0.010 0.669
T1Dstatus 1 1.3 1.253 9.47 0.027 0.002 **
Days 1 0.3 0.259 1.96 0.006 0.079 .
seqRun 4 1.8 0.444 3.35 0.038 0.212
Age 1 0.5 0.518 3.91 0.011 0.851
Parity 1 0.3 0.259 1.96 0.006 0.995
BMI 1 0.1 0.110 0.83 0.002 0.182
AG15 1 0.5 0.501 3.78 0.011 0.091 .
Residuals 312 41.3 0.132 0.889 0.011 *
Total 324 46.5 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 16.1.9.9 Pre-eclampsia (within T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.68 0.338 2.95 0.023 0.18
Days 1 0.16 0.156 1.36 0.005 0.16
seqRun 4 1.89 0.471 4.12 0.065 0.81
Age 1 0.27 0.274 2.39 0.009 0.47
Parity 1 0.24 0.244 2.13 0.008 0.65
BMI 1 0.25 0.249 2.17 0.009 0.11
Preeclampsia 1 0.13 0.133 1.16 0.005 0.26
Residuals 223 25.52 0.114 0.876 0.25
Total 234 29.14 1.000 6.2 Differential abundance analysis Genus taxonomic level
Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type
nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down 0 0 0 0 0 1 1 0 0 0
NotSig 50 50 50 51 52 51 51 52 52 52
Up 2 2 2 1 0 0 0 0 0 0
noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down 0 0 1
NotSig 52 52 51
Up 0 0 0Results for contrasts with significant differentially abundant strains shown below
6.2.1 Across all trimesters (T1D vs non-T1D)
[1] Classification LogFC P.Val adj.P.Val nonT1D:mean%
[6] Prev% T1D:mean% T1D:Prev% Feature
<0 rows> (or 0-length row.names)6.2.2 Only Trimester 1 (nonT1D vs T1D)
[1] Classification LogFC P.Val adj.P.Val nonT1D:mean%
[6] Prev% T1D:mean% T1D:Prev%
<0 rows> (or 0-length row.names)6.2.3 Only Trimester 2 (nonT1D vs T1D)
[1] Classification LogFC P.Val adj.P.Val nonT1D:mean%
[6] Prev% T1D:mean% T1D:Prev%
<0 rows> (or 0-length row.names)6.2.4 Only Trimester 3 (nonT1D vs T1D)
[1] Classification LogFC P.Val adj.P.Val nonT1D:mean%
[6] Prev% T1D:mean% T1D:Prev%
<0 rows> (or 0-length row.names)6.2.5 T1 vs T2 (T1D and non-T1D data)
[1] "No DA taxa"6.2.6 T2 vs T3 (T1D and non-T1D data)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Oscillibacter -0.531 0.000484 0.0252 0.077 50.0
2 Oscillibacter -0.531 0.000484 0.0252 0.070 42.4
3 Oscillibacter -0.531 0.000484 0.0252 0.115 55.7Nothing left after filtering by prevalence and LogFC
6.2.7 T1 vs T3 (T1D and non-T1D data)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Oscillibacter -0.815 0.000186 0.00968 0.077 50.0
2 Oscillibacter -0.815 0.000186 0.00968 0.070 42.4
3 Oscillibacter -0.815 0.000186 0.00968 0.115 55.76.2.8 T1 vs T2 (in women with T1D)
[1] "No DA taxa"6.2.9 T2 vs T3 (in women with T1D)
[1] "No DA taxa"6.2.10 T1 vs T3 (in women with T1D)
[1] "No DA taxa"6.2.11 T1 vs T2 (in women without T1D)
[1] "No DA taxa"6.2.12 T2 vs T3 (in women without T1D)
[1] "No DA taxa"6.2.13 T1 vs T3 (in women without T1D)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Oscillibacter -1.26 0.000439 0.0228 0.028 33.3
2 Oscillibacter -1.26 0.000439 0.0228 0.156 60.07 Family taxonomic level
7.1 Microbial community composition analysis at Family level (Beta diversity analysis)
7.1.1 Interaction between T1D status and Time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 5 1.8 0.360 3.32 0.044 0.566
Days 1 0.2 0.224 2.07 0.005 0.040 *
T1D_Time_Interaction 1 1.0 0.999 9.22 0.024 0.043 *
Age 1 0.3 0.266 2.46 0.006 0.742
Parity 1 0.2 0.172 1.59 0.004 0.999
BMI 1 0.2 0.226 2.08 0.006 0.415
HLA 2 0.4 0.194 1.79 0.009 0.567
T1Dstatus 1 0.1 0.060 0.55 0.001 0.966
Residuals 340 36.9 0.108 0.899 0.761
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.0437.1.2 T1D status in trimester 1
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 3 0.34 0.115 1.080 0.057 0.38
Nulliparous 1 0.13 0.132 1.248 0.022 0.28
Age_LMP 1 0.15 0.152 1.430 0.025 0.19
BMI_conception 1 0.09 0.086 0.812 0.014 0.56
HLA.6DRML 2 0.25 0.125 1.176 0.042 0.31
T1Dstatus 1 0.16 0.156 1.473 0.026 0.21
Residuals 46 4.87 0.106 0.813
Total 55 5.99 1.000 [1] 0.212Beta diversity Plot
7.1.3 T1D status in trimester 2
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 4 0.58 0.145 1.26 0.038 0.212
Nulliparous 1 0.08 0.082 0.72 0.005 0.607
Age_LMP 1 0.18 0.178 1.55 0.012 0.139
BMI_conception 1 0.19 0.193 1.68 0.013 0.118
HLA.6DRML 2 0.20 0.098 0.86 0.013 0.592
T1Dstatus 1 0.46 0.456 3.97 0.030 0.004 **
Residuals 117 13.42 0.115 0.889
Total 127 15.10 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.004Beta diversity Plot
7.1.4 T1D status in trimester 3
Call:
adonis(formula = D ~ SeqRun + Nulliparous + Age_LMP + BMI_conception + HLA.6DRML + T1Dstatus, data = Meta_dfTri)
Permutation: free
Number of permutations: 999
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
SeqRun 5 0.88 0.175 1.59 0.058 0.081 .
Nulliparous 1 0.19 0.187 1.70 0.012 0.133
Age_LMP 1 0.17 0.165 1.50 0.011 0.182
BMI_conception 1 0.17 0.169 1.53 0.011 0.160
HLA.6DRML 2 0.18 0.088 0.80 0.012 0.611
T1Dstatus 1 0.44 0.441 4.00 0.029 0.007 **
Residuals 119 13.12 0.110 0.867
Total 130 15.14 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.007Beta diversity Plot
7.1.5 Days within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.53 0.265 2.81 0.022 0.258
seqRun 4 1.73 0.432 4.57 0.071 0.931
Age 1 0.18 0.182 1.92 0.008 0.067 .
Parity 1 0.16 0.162 1.71 0.007 0.821
BMI 1 0.31 0.307 3.25 0.013 0.318
Days 1 0.13 0.131 1.39 0.005 0.030 *
Residuals 224 21.16 0.094 0.874 0.299
Total 234 24.20 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
7.1.6 Trimester within T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.53 0.265 2.79 0.022 0.237
seqRun 4 1.73 0.432 4.55 0.071 0.927
Age 1 0.18 0.182 1.91 0.008 0.066 .
Parity 1 0.16 0.162 1.70 0.007 0.799
BMI 1 0.31 0.307 3.23 0.013 0.326
Tri 2 0.12 0.062 0.65 0.005 0.268
Residuals 223 21.17 0.095 0.875 0.418
Total 234 24.20 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
7.1.7 Days within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.52 0.258 1.99 0.032 0.528
seqRun 5 0.65 0.131 1.01 0.041 0.831
Age 1 0.50 0.499 3.85 0.031 0.396
Parity 1 0.25 0.253 1.95 0.016 0.049 *
BMI 1 0.09 0.092 0.71 0.006 0.543
Days 1 0.09 0.094 0.72 0.006 0.340
Residuals 107 13.87 0.130 0.868 0.732
Total 118 15.97 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
7.1.8 Trimester within non-T1D
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.52 0.258 1.97 0.032 0.501
seqRun 5 0.65 0.131 1.00 0.041 0.827
Age 1 0.50 0.499 3.81 0.031 0.383
Parity 1 0.25 0.253 1.94 0.016 0.035 *
BMI 1 0.09 0.092 0.70 0.006 0.560
Tri 2 0.10 0.048 0.37 0.006 0.894
Residuals 106 13.86 0.131 0.868 0.803
Total 118 15.97 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1Beta diversity Plot
7.1.9 Other factors
7.1.9.1 Age at conception
7.1.9.1.1 Age at conception interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.58 0.008 0.732
T1Dstatus 1 1.0 0.979 9.01 0.024 0.003 **
seqRun 5 1.9 0.373 3.44 0.046 0.551
Tri 2 0.1 0.073 0.67 0.004 0.302
Age 1 0.3 0.322 2.96 0.008 0.828
Parity 1 0.2 0.159 1.46 0.004 0.986
BMI 1 0.2 0.211 1.95 0.005 0.913
Age_Time_Interaction 1 0.2 0.153 1.40 0.004 0.344
Residuals 339 36.8 0.109 0.898 0.179
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.1.2 Age at conception interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.58 0.008 0.720
T1Dstatus 1 1.0 0.979 8.99 0.024 0.006 **
seqRun 5 1.9 0.373 3.43 0.046 0.543
Tri 2 0.1 0.073 0.67 0.004 0.309
Age 1 0.3 0.322 2.96 0.008 0.823
Parity 1 0.2 0.159 1.46 0.004 0.976
BMI 1 0.2 0.211 1.94 0.005 0.906
Age_Time_Interaction 1 0.1 0.069 0.63 0.002 0.500
Residuals 339 36.9 0.109 0.900 0.193
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.1.3 Age at conception interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.58 0.008 0.737
T1Dstatus 1 1.0 0.979 8.98 0.024 0.003 **
seqRun 5 1.9 0.373 3.43 0.046 0.533
Tri 2 0.1 0.073 0.67 0.004 0.289
Age 1 0.3 0.322 2.95 0.008 0.836
Parity 1 0.2 0.159 1.46 0.004 0.984
BMI 1 0.2 0.211 1.94 0.005 0.922
Age_Time_Interaction 1 0.0 0.031 0.28 0.001 0.784
Residuals 339 36.9 0.109 0.901 0.225
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.1.4 Age at conception (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.58 0.008 0.700
T1Dstatus 1 1.0 0.979 9.00 0.024 0.001 ***
seqRun 5 1.9 0.373 3.43 0.046 0.526
Tri 2 0.1 0.073 0.67 0.004 0.316
Parity 1 0.2 0.155 1.43 0.004 0.996
BMI 1 0.2 0.210 1.93 0.005 0.920
Age 1 0.3 0.327 3.01 0.008 0.672
Residuals 340 37.0 0.109 0.902 0.181
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.2 Body max index (BMI)
7.1.9.2.1 BMI interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.58 0.008 0.730
T1Dstatus 1 1.0 0.979 8.99 0.024 0.006 **
seqRun 5 1.9 0.373 3.43 0.046 0.566
Tri 2 0.1 0.073 0.67 0.004 0.302
Age 1 0.3 0.322 2.95 0.008 0.826
Parity 1 0.2 0.159 1.46 0.004 0.984
BMI 1 0.2 0.211 1.94 0.005 0.907
BMI_Time_Interaction 1 0.0 0.045 0.42 0.001 0.757
Residuals 339 36.9 0.109 0.901 0.228
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.2.2 BMI interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.58 0.008 0.740
T1Dstatus 1 1.0 0.979 9.00 0.024 0.003 **
seqRun 5 1.9 0.373 3.43 0.046 0.556
Tri 2 0.1 0.073 0.67 0.004 0.313
Age 1 0.3 0.322 2.96 0.008 0.843
Parity 1 0.2 0.159 1.46 0.004 0.974
BMI 1 0.2 0.211 1.94 0.005 0.918
BMI_Time_Interaction 1 0.1 0.078 0.72 0.002 0.409
Residuals 339 36.9 0.109 0.900 0.193
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.2.3 BMI (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.58 0.008 0.731
T1Dstatus 1 1.0 0.979 8.99 0.024 0.003 **
seqRun 5 1.9 0.373 3.43 0.046 0.531
Tri 2 0.1 0.073 0.67 0.004 0.285
Age 1 0.3 0.322 2.96 0.008 0.840
Parity 1 0.2 0.159 1.46 0.004 0.982
BMI 1 0.2 0.211 1.94 0.005 0.908
BMI_Time_Interaction 1 0.1 0.054 0.49 0.001 0.547
Residuals 339 36.9 0.109 0.900 0.190
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.2.4 BMI (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.58 0.008 0.757
T1Dstatus 1 1.0 0.979 9.00 0.024 0.002 **
seqRun 5 1.9 0.373 3.43 0.046 0.529
Tri 2 0.1 0.073 0.67 0.004 0.316
Age 1 0.3 0.322 2.96 0.008 0.822
Parity 1 0.2 0.159 1.46 0.004 0.974
BMI 1 0.2 0.211 1.94 0.005 0.910
Residuals 340 37.0 0.109 0.902 0.193
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.3 HLA type
7.1.9.3.1 HLA type interaction with time (reference: DR34 )
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.59 0.008 0.722
T1Dstatus 1 1.0 0.979 9.04 0.024 0.004 **
Days 1 0.2 0.227 2.10 0.006 0.086 .
seqRun 5 1.9 0.372 3.43 0.045 0.531
Age 1 0.3 0.309 2.86 0.008 0.818
Parity 1 0.2 0.153 1.41 0.004 0.994
BMI 1 0.2 0.205 1.89 0.005 0.936
HLA_Time_Interaction 1 0.1 0.099 0.91 0.002 0.972
Residuals 340 36.8 0.108 0.898 0.154
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.3.2 HLA type interaction with time (reference: DRXX)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.58 0.008 0.709
T1Dstatus 1 1.0 0.979 9.02 0.024 0.006 **
Days 1 0.2 0.227 2.09 0.006 0.091 .
seqRun 5 1.9 0.372 3.42 0.045 0.577
Age 1 0.3 0.309 2.85 0.008 0.811
Parity 1 0.2 0.153 1.41 0.004 0.989
BMI 1 0.2 0.205 1.89 0.005 0.936
HLA_Time_Interaction 1 0.0 0.008 0.07 0.000 1.000
Residuals 340 36.9 0.109 0.900 0.195
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.3.3 HLA type interaction with time (reference: Group3o4)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.59 0.008 0.735
T1Dstatus 1 1.0 0.979 9.03 0.024 0.006 **
Days 1 0.2 0.227 2.10 0.006 0.098 .
seqRun 5 1.9 0.372 3.43 0.045 0.565
Age 1 0.3 0.309 2.85 0.008 0.791
Parity 1 0.2 0.153 1.41 0.004 0.991
BMI 1 0.2 0.205 1.89 0.005 0.934
HLA_Time_Interaction 1 0.1 0.056 0.52 0.001 1.000
Residuals 340 36.9 0.108 0.899 0.218
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.3.4 HLA type (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.2 0.246 2.27 0.006 0.068 .
seqRun 5 1.8 0.356 3.29 0.043 0.623
Age 1 0.3 0.345 3.19 0.008 0.565
Parity 1 0.2 0.189 1.75 0.005 0.990
BMI 1 0.3 0.260 2.40 0.006 0.152
T1Dstatus 1 0.8 0.850 7.85 0.021 0.006 **
HLA 2 0.4 0.203 1.87 0.010 0.577
Residuals 341 36.9 0.108 0.901 0.129
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.4 Parity
7.1.9.4.1 Parity interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.59 0.008 0.724
T1Dstatus 1 1.0 0.979 9.04 0.024 0.002 **
Days 1 0.2 0.227 2.10 0.006 0.105
seqRun 5 1.9 0.372 3.43 0.045 0.537
Age 1 0.3 0.309 2.86 0.008 0.809
Parity 1 0.2 0.153 1.41 0.004 0.990
BMI 1 0.2 0.205 1.89 0.005 0.939
Parity_Time_Interaction 1 0.1 0.113 1.05 0.003 0.068 .
Residuals 340 36.8 0.108 0.898 0.107
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.4.2 Parity (no interaction but within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.24 0.1222 1.150 0.041 0.329
T1Dstatus 1 0.11 0.1066 1.003 0.018 0.407
seqRun 1 0.23 0.2273 2.139 0.038 0.012 *
Age 1 0.19 0.1908 1.796 0.032 0.156
BMI 1 0.07 0.0679 0.639 0.011 0.894
Parity 1 0.09 0.0949 0.894 0.016 0.147
Residuals 48 5.10 0.1063 0.846 0.133
Total 55 6.03 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.4.3 Parity (no interaction but within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.21 0.107 0.94 0.011 0.735
T1Dstatus 1 0.52 0.516 4.56 0.028 0.018 *
seqRun 1 0.59 0.595 5.25 0.032 0.110
Age 1 0.15 0.154 1.36 0.008 0.968
BMI 1 0.13 0.132 1.17 0.007 0.328
Parity 1 0.07 0.073 0.65 0.004 0.989
Residuals 150 16.99 0.113 0.910 0.106
Total 157 18.68 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.4.4 Parity (no interaction but within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.21 0.107 0.97 0.013 0.618
T1Dstatus 1 0.45 0.449 4.09 0.028 0.012 *
seqRun 1 0.57 0.572 5.22 0.035 0.232
Age 1 0.12 0.120 1.10 0.007 0.795
BMI 1 0.09 0.094 0.86 0.006 0.873
Parity 1 0.22 0.224 2.04 0.014 0.818
Residuals 132 14.48 0.110 0.896 0.059 .
Total 139 16.16 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.5 Mode of delivery
7.1.9.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.61 0.008 0.726
T1Dstatus 1 1.0 0.979 9.17 0.024 0.003 **
MOD 2 0.6 0.309 2.90 0.015 0.245
Days 1 0.2 0.228 2.14 0.006 0.115
seqRun 5 1.9 0.384 3.60 0.047 0.522
Age 1 0.4 0.438 4.10 0.011 0.050 *
Parity 1 0.1 0.147 1.38 0.004 0.979
BMI 1 0.2 0.153 1.44 0.004 0.989
MOD_Time_Interaction 1 0.1 0.094 0.88 0.002 0.947
Residuals 338 36.1 0.107 0.880 0.074 .
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.5.2 Mode of delivery interaction with time (reference: Elective caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.62 0.008 0.726
T1Dstatus 1 1.0 0.979 9.20 0.024 0.002 **
MOD 2 0.6 0.309 2.90 0.015 0.234
Days 1 0.2 0.228 2.14 0.006 0.096 .
seqRun 5 1.9 0.384 3.61 0.047 0.528
Age 1 0.4 0.438 4.11 0.011 0.055 .
Parity 1 0.1 0.147 1.38 0.004 0.978
BMI 1 0.2 0.153 1.44 0.004 0.988
MOD_Time_Interaction 1 0.2 0.180 1.69 0.004 1.000
Residuals 338 36.0 0.106 0.878 0.295
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.5.3 Mode of delivery interaction with time (reference: Labour)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.61 0.008 0.717
T1Dstatus 1 1.0 0.979 9.17 0.024 0.001 ***
MOD 2 0.6 0.309 2.90 0.015 0.241
Days 1 0.2 0.228 2.14 0.006 0.109
seqRun 5 1.9 0.384 3.60 0.047 0.513
Age 1 0.4 0.438 4.10 0.011 0.061 .
Parity 1 0.1 0.147 1.38 0.004 0.987
BMI 1 0.2 0.153 1.44 0.004 0.991
MOD_Time_Interaction 1 0.1 0.073 0.69 0.002 1.000
Residuals 338 36.1 0.107 0.880 0.416
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.5.4 Mode of delivery (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.2 0.246 2.30 0.006 0.066 .
seqRun 5 1.8 0.356 3.34 0.043 0.595
Age 1 0.3 0.345 3.23 0.008 0.586
Parity 1 0.2 0.189 1.77 0.005 0.994
BMI 1 0.3 0.260 2.43 0.006 0.162
HLA 2 0.3 0.153 1.43 0.007 0.777
T1Dstatus 1 0.9 0.950 8.90 0.023 0.005 **
MOD 2 0.8 0.377 3.53 0.018 0.102
Residuals 339 36.2 0.107 0.882 0.054 .
Total 353 41.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.6 Carbohydrate intake
7.1.9.6.1 Carbohydrate interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.63 0.009 0.711
T1Dstatus 1 0.6 0.650 6.16 0.018 0.025 *
Carbs 1 0.3 0.305 2.89 0.008 0.270
seqRun 5 2.0 0.400 3.79 0.054 0.689
Tri 2 0.1 0.051 0.48 0.003 0.443
Age 1 0.3 0.320 3.04 0.009 0.771
Parity 1 0.2 0.183 1.73 0.005 0.953
BMI 1 0.2 0.236 2.24 0.006 0.668
Carb_Time_Interaction 1 0.2 0.179 1.69 0.005 0.010 **
Residuals 310 32.7 0.106 0.883 0.403
Total 325 37.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.6.2 Carbohydrate interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.63 0.009 0.722
T1Dstatus 1 0.6 0.650 6.16 0.018 0.033 *
Carbs 1 0.3 0.305 2.89 0.008 0.266
seqRun 5 2.0 0.400 3.79 0.054 0.717
Tri 2 0.1 0.051 0.48 0.003 0.485
Age 1 0.3 0.320 3.04 0.009 0.766
Parity 1 0.2 0.183 1.73 0.005 0.947
BMI 1 0.2 0.236 2.24 0.006 0.653
Carb_Time_Interaction 1 0.2 0.182 1.73 0.005 0.097 .
Residuals 310 32.7 0.106 0.883 0.473
Total 325 37.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.6.3 Carbohydrate interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.63 0.009 0.715
T1Dstatus 1 0.6 0.650 6.15 0.018 0.027 *
Carbs 1 0.3 0.305 2.88 0.008 0.247
seqRun 5 2.0 0.400 3.79 0.054 0.700
Tri 2 0.1 0.051 0.48 0.003 0.463
Age 1 0.3 0.320 3.03 0.009 0.770
Parity 1 0.2 0.183 1.73 0.005 0.946
BMI 1 0.2 0.236 2.24 0.006 0.677
Carb_Time_Interaction 1 0.1 0.138 1.30 0.004 0.055 .
Residuals 310 32.8 0.106 0.884 0.440
Total 325 37.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.6.4 Carbohydrate (no interaction within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.37 0.125 1.172 0.070 0.003 **
Age 1 0.14 0.143 1.341 0.027 0.003 **
Parity 1 0.11 0.106 0.997 0.020 0.003 **
BMI 1 0.10 0.101 0.942 0.019 0.001 ***
HLA 2 0.25 0.127 1.188 0.047 0.294
T1Dstatus 1 0.14 0.142 1.335 0.026 0.243
Carbs 1 0.11 0.105 0.985 0.020 0.422
Residuals 39 4.16 0.107 0.772 0.273
Total 49 5.38 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.6.5 Carbohydrate (no interaction within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 1.04 0.260 2.411 0.063 0.001 ***
Age 1 0.19 0.195 1.809 0.012 0.847
Parity 1 0.12 0.121 1.127 0.007 0.846
BMI 1 0.14 0.136 1.263 0.008 0.925
HLA 2 0.15 0.077 0.719 0.009 0.911
T1Dstatus 1 0.33 0.331 3.069 0.020 0.045 *
Carbs 1 0.28 0.276 2.563 0.017 0.074 .
Residuals 132 14.22 0.108 0.863 0.154
Total 143 16.47 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.6.6 Carbohydrate (no interaction within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 0.88 0.2211 2.021 0.059 0.58
Age 1 0.14 0.1405 1.284 0.009 0.35
Parity 1 0.19 0.1883 1.721 0.012 0.92
BMI 1 0.15 0.1536 1.404 0.010 0.31
HLA 2 0.16 0.0778 0.711 0.010 0.81
T1Dstatus 1 0.31 0.3148 2.877 0.021 0.04 *
Carbs 1 0.11 0.1080 0.987 0.007 0.48
Residuals 120 13.13 0.1094 0.871 0.67
Total 131 15.08 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.7 Fibre intake
7.1.9.7.1 Fibre interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.64 0.009 0.709
T1Dstatus 1 0.6 0.650 6.19 0.018 0.024 *
Fiber 1 0.3 0.253 2.41 0.007 0.363
seqRun 5 2.2 0.447 4.26 0.060 0.520
Tri 2 0.1 0.049 0.47 0.003 0.506
Age 1 0.3 0.320 3.05 0.009 0.770
Parity 1 0.2 0.174 1.66 0.005 0.981
BMI 1 0.2 0.215 2.05 0.006 0.833
Fiber_Time_Interaction 1 0.2 0.202 1.93 0.005 0.001 ***
Residuals 310 32.5 0.105 0.879 0.228
Total 325 37.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.7.2 Fibre interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.64 0.009 0.725
T1Dstatus 1 0.6 0.650 6.18 0.018 0.027 *
Fiber 1 0.3 0.253 2.41 0.007 0.360
seqRun 5 2.2 0.447 4.25 0.060 0.500
Tri 2 0.1 0.049 0.47 0.003 0.467
Age 1 0.3 0.320 3.05 0.009 0.787
Parity 1 0.2 0.174 1.66 0.005 0.975
BMI 1 0.2 0.215 2.04 0.006 0.826
Fiber_Time_Interaction 1 0.1 0.138 1.31 0.004 0.842
Residuals 310 32.6 0.105 0.880 0.438
Total 325 37.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.7.3 Fibre interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.3 0.172 1.64 0.009 0.727
T1Dstatus 1 0.6 0.650 6.18 0.018 0.026 *
Fiber 1 0.3 0.253 2.41 0.007 0.356
seqRun 5 2.2 0.447 4.25 0.060 0.490
Tri 2 0.1 0.049 0.47 0.003 0.506
Age 1 0.3 0.320 3.05 0.009 0.750
Parity 1 0.2 0.174 1.66 0.005 0.972
BMI 1 0.2 0.215 2.05 0.006 0.841
Fiber_Time_Interaction 1 0.2 0.187 1.78 0.005 0.531
Residuals 310 32.6 0.105 0.879 0.362
Total 325 37.0 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.7.4 Fibre (no interaction within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.37 0.125 1.154 0.070 0.005 **
Age 1 0.14 0.143 1.321 0.027 0.005 **
Parity 1 0.11 0.106 0.982 0.020 0.005 **
BMI 1 0.10 0.101 0.928 0.019 0.001 ***
HLA 2 0.25 0.127 1.170 0.047 0.296
T1Dstatus 1 0.14 0.142 1.315 0.026 0.231
Fiber 1 0.04 0.043 0.397 0.008 0.864
Residuals 39 4.22 0.108 0.784 0.412
Total 49 5.38 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.7.5 Fibre (no interaction within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 1.04 0.260 2.393 0.063 0.001 ***
Age 1 0.19 0.195 1.796 0.012 0.847
Parity 1 0.12 0.121 1.119 0.007 0.854
BMI 1 0.14 0.136 1.253 0.008 0.929
HLA 2 0.15 0.077 0.714 0.009 0.911
T1Dstatus 1 0.33 0.331 3.046 0.020 0.054 .
Fiber 1 0.17 0.168 1.550 0.010 0.303
Residuals 132 14.33 0.109 0.870 0.314
Total 143 16.47 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.7.6 Fibre (no interaction within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 0.88 0.221 2.07 0.059 0.514
Age 1 0.14 0.140 1.32 0.009 0.389
Parity 1 0.19 0.188 1.76 0.012 0.916
BMI 1 0.15 0.154 1.44 0.010 0.333
HLA 2 0.16 0.078 0.73 0.010 0.792
T1Dstatus 1 0.31 0.315 2.95 0.021 0.040 *
Fiber 1 0.42 0.423 3.96 0.028 0.006 **
Residuals 120 12.82 0.107 0.850 0.413
Total 131 15.08 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.8 1,5-AG (glucose control measurement)
7.1.9.8.1 1,5-AG interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.178 1.66 0.009 0.705
T1Dstatus 1 1.0 1.050 9.78 0.028 0.002 **
Days 1 0.2 0.229 2.14 0.006 0.018 *
seqRun 4 1.6 0.402 3.74 0.043 0.090 .
Age 1 0.4 0.365 3.40 0.010 0.733
Parity 1 0.1 0.148 1.38 0.004 0.992
BMI 1 0.2 0.165 1.54 0.004 0.929
AG15 1 0.3 0.331 3.08 0.009 0.340
AG15_T1D_Interaction 1 0.2 0.152 1.42 0.004 1.000
Residuals 311 33.4 0.107 0.883 0.088 .
Total 324 37.8 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.8.2 1,5-AG within T1D women
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.56 0.281 3.00 0.026 0.181
Days 1 0.17 0.168 1.80 0.008 0.011 *
seqRun 4 1.42 0.355 3.79 0.065 0.984
Age 1 0.18 0.183 1.96 0.008 0.035 *
Parity 1 0.14 0.137 1.47 0.006 0.730
BMI 1 0.26 0.256 2.74 0.012 0.255
AG15 1 0.21 0.209 2.23 0.010 0.686
Residuals 202 18.89 0.094 0.866 0.288
Total 213 21.83 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.8.3 1,5-AG interaction with time (within non-T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.58 0.290 2.28 0.038 0.447
Days 1 0.18 0.181 1.42 0.012 0.128
seqRun 3 0.45 0.152 1.19 0.030 0.936
Age 1 0.51 0.508 3.99 0.034 0.558
Parity 1 0.26 0.256 2.01 0.017 0.069 .
BMI 1 0.07 0.070 0.55 0.005 0.870
AG15 1 0.29 0.293 2.30 0.019 0.234
Residuals 100 12.73 0.127 0.845 0.413
Total 110 15.08 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.8.4 1,5-AG (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.4 0.178 1.66 0.009 0.696
T1Dstatus 1 1.0 1.050 9.77 0.028 0.003 **
Days 1 0.2 0.229 2.13 0.006 0.024 *
seqRun 4 1.6 0.402 3.74 0.043 0.091 .
Age 1 0.4 0.365 3.40 0.010 0.721
Parity 1 0.1 0.148 1.38 0.004 0.992
BMI 1 0.2 0.165 1.54 0.004 0.926
AG15 1 0.3 0.331 3.08 0.009 0.372
Residuals 312 33.5 0.107 0.887 0.015 *
Total 324 37.8 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.1.9.9 Pre-eclampsia (within T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.53 0.265 2.81 0.022 0.256
Days 1 0.14 0.138 1.46 0.006 0.036 *
seqRun 4 1.71 0.429 4.54 0.071 0.943
Age 1 0.17 0.171 1.81 0.007 0.127
Parity 1 0.16 0.161 1.71 0.007 0.821
BMI 1 0.32 0.324 3.44 0.013 0.160
Preeclampsia 1 0.11 0.108 1.14 0.004 0.365
Residuals 223 21.05 0.094 0.870 0.295
Total 234 24.20 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 17.2 Differential abundance analysis Family taxonomic level
Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type
nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down 0 0 0 0 0 0 0 1 1 2
NotSig 33 33 25 33 33 33 32 32 32 31
Up 0 0 8 0 0 0 1 0 0 0
noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down 0 0 0
NotSig 33 31 33
Up 0 2 0Results for contrasts with significant (or borderline significant) differences shown below
7.2.1 Across all trimesters (T1D vs non-T1D)
[1] Classification LogFC P.Val adj.P.Val nonT1D:mean%
[6] Prev% T1D:mean% T1D:Prev% Feature
<0 rows> (or 0-length row.names)7.2.2 Only Trimester 1 (nonT1D vs T1D)
Classification LogFC P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
1 Desulfovibrionaceae 1.63 0.00364 0.0601 0.353 83.3 0.154 65.87.2.3 Only Trimester 2 (nonT1D vs T1D)
Classification LogFC P.Val adj.P.Val nonT1D:mean% Prev% T1D:mean% T1D:Prev%
1 Lachnospiraceae 0.53 0.00878 0.0483 17.3 100 15.3 1007.2.4 Only Trimester 3 (nonT1D vs T1D)
[1] "No DA taxa"7.2.5 T1 vs T2 (T1D and non-T1D data)
[1] "No DA taxa"7.2.6 T2 vs T3 (T1D and non-T1D data)
[1] "No DA taxa"Nothing left after filtering by prevalence and LogFC
7.2.7 T1 vs T3 (T1D and non-T1D data)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Pasteurellaceae 0.835 0.00095 0.0313 0.095 33.9
2 Pasteurellaceae 0.835 0.00095 0.0313 0.081 32.3
3 Pasteurellaceae 0.835 0.00095 0.0313 0.061 27.17.2.8 T1 vs T2 (in women with T1D)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Clostridiaceae 1 -1.01 0.00143 0.0473 0.187 44.7
2 Clostridiaceae 1 -1.01 0.00143 0.0473 0.458 59.87.2.9 T2 vs T3 (in women with T1D)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Peptococcaceae -0.543 0.000111 0.00366 0.007 10.3
2 Peptococcaceae -0.543 0.000111 0.00366 0.025 23.37.2.10 T1 vs T3 (in women with T1D)
Classification LogFC P.Val adj.P.Val T1:mean% T1Prev% T3:mean% T3Prev%
1 Bacteroidaceae -0.533 0.00216 0.0357 32.5 97.4 35.4 1007.2.11 T1 vs T2 (in women without T1D)
[1] "No DA taxa"7.2.12 T2 vs T3 (in women without T1D)
[1] Classification LogFC P.Val adj.P.Val T2:mean%
[6] T2Prev% T3:mean% T3Prev%
<0 rows> (or 0-length row.names)7.2.13 T1 vs T3 (in women without T1D)
[1] "No DA taxa"8 Order taxonomic level
8.1 Microbial community composition analysis at Order level (Beta diversity analysis)
8.1.1 Interaction between T1D status and Time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 5 0.90 0.1798 4.54 0.060 0.83
Days 1 0.10 0.0966 2.44 0.006 0.10
T1D_Time_Interaction 1 0.07 0.0661 1.67 0.004 0.16
Age 1 0.03 0.0257 0.65 0.002 0.65
Parity 1 0.13 0.1336 3.37 0.009 0.98
BMI 1 0.11 0.1094 2.76 0.007 0.58
HLA 2 0.11 0.0568 1.43 0.008 0.51
T1Dstatus 1 0.02 0.0160 0.40 0.001 0.86
Residuals 340 13.47 0.0396 0.902 0.77
Total 353 14.93 1.000 [1] 0.1568.1.2 Other factors
8.1.2.1 Age at conception
8.1.2.1.1 Age at conception interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.86 0.010 0.43
T1Dstatus 1 0.06 0.0608 1.54 0.004 0.42
seqRun 5 0.91 0.1826 4.62 0.061 0.67
Tri 2 0.07 0.0333 0.84 0.004 0.22
Age 1 0.03 0.0288 0.73 0.002 0.41
Parity 1 0.12 0.1174 2.97 0.008 0.97
BMI 1 0.10 0.0969 2.45 0.006 0.83
Age_Time_Interaction 1 0.10 0.0998 2.53 0.007 0.17
Residuals 339 13.40 0.0395 0.898 0.67
Total 353 14.93 1.000 8.1.2.1.2 Age at conception interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.86 0.010 0.47
T1Dstatus 1 0.06 0.0608 1.54 0.004 0.44
seqRun 5 0.91 0.1826 4.62 0.061 0.64
Tri 2 0.07 0.0333 0.84 0.004 0.23
Age 1 0.03 0.0288 0.73 0.002 0.38
Parity 1 0.12 0.1174 2.97 0.008 0.97
BMI 1 0.10 0.0969 2.45 0.006 0.82
Age_Time_Interaction 1 0.10 0.0954 2.41 0.006 0.17
Residuals 339 13.40 0.0395 0.898 0.66
Total 353 14.93 1.000 8.1.2.1.3 Age at conception interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.84 0.010 0.42
T1Dstatus 1 0.06 0.0608 1.53 0.004 0.43
seqRun 5 0.91 0.1826 4.59 0.061 0.65
Tri 2 0.07 0.0333 0.84 0.004 0.22
Age 1 0.03 0.0288 0.72 0.002 0.34
Parity 1 0.12 0.1174 2.95 0.008 0.97
BMI 1 0.10 0.0969 2.43 0.006 0.83
Age_Time_Interaction 1 0.01 0.0092 0.23 0.001 0.66
Residuals 339 13.49 0.0398 0.904 0.80
Total 353 14.93 1.000 8.1.2.1.4 Age at conception (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.85 0.010 0.44
T1Dstatus 1 0.06 0.0608 1.53 0.004 0.45
seqRun 5 0.91 0.1826 4.60 0.061 0.68
Tri 2 0.07 0.0333 0.84 0.004 0.23
Parity 1 0.12 0.1155 2.91 0.008 0.98
BMI 1 0.10 0.0960 2.42 0.006 0.84
Age 1 0.03 0.0315 0.79 0.002 0.24
Residuals 340 13.50 0.0397 0.904 0.79
Total 353 14.93 1.000 8.1.2.2 Body max index (BMI)
8.1.2.2.1 BMI interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.84 0.010 0.44
T1Dstatus 1 0.06 0.0608 1.53 0.004 0.42
seqRun 5 0.91 0.1826 4.59 0.061 0.69
Tri 2 0.07 0.0333 0.84 0.004 0.22
Age 1 0.03 0.0288 0.72 0.002 0.39
Parity 1 0.12 0.1174 2.95 0.008 0.97
BMI 1 0.10 0.0969 2.43 0.006 0.80
BMI_Time_Interaction 1 0.00 0.0037 0.09 0.000 0.96
Residuals 339 13.49 0.0398 0.904 0.88
Total 353 14.93 1.000 8.1.2.2.2 BMI interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.85 0.010 0.41
T1Dstatus 1 0.06 0.0608 1.53 0.004 0.46
seqRun 5 0.91 0.1826 4.60 0.061 0.66
Tri 2 0.07 0.0333 0.84 0.004 0.22
Age 1 0.03 0.0288 0.72 0.002 0.35
Parity 1 0.12 0.1174 2.96 0.008 0.98
BMI 1 0.10 0.0969 2.44 0.006 0.82
BMI_Time_Interaction 1 0.04 0.0416 1.05 0.003 0.55
Residuals 339 13.46 0.0397 0.901 0.81
Total 353 14.93 1.000 8.1.2.2.3 BMI (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.85 0.010 0.47
T1Dstatus 1 0.06 0.0608 1.53 0.004 0.40
seqRun 5 0.91 0.1826 4.60 0.061 0.64
Tri 2 0.07 0.0333 0.84 0.004 0.22
Age 1 0.03 0.0288 0.72 0.002 0.36
Parity 1 0.12 0.1174 2.96 0.008 0.97
BMI 1 0.10 0.0969 2.44 0.006 0.83
BMI_Time_Interaction 1 0.04 0.0436 1.10 0.003 0.12
Residuals 339 13.45 0.0397 0.901 0.72
Total 353 14.93 1.000 8.1.2.2.4 BMI (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.85 0.010 0.46
T1Dstatus 1 0.06 0.0608 1.53 0.004 0.44
seqRun 5 0.91 0.1826 4.60 0.061 0.65
Tri 2 0.07 0.0333 0.84 0.004 0.23
Age 1 0.03 0.0288 0.72 0.002 0.37
Parity 1 0.12 0.1174 2.96 0.008 0.96
BMI 1 0.10 0.0969 2.44 0.006 0.81
Residuals 340 13.50 0.0397 0.904 0.78
Total 353 14.93 1.000 8.1.2.3 HLA type
8.1.2.3.1 HLA type interaction with time (reference: DR34 )
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.85 0.010 0.43
T1Dstatus 1 0.06 0.0608 1.54 0.004 0.43
Days 1 0.07 0.0695 1.76 0.005 0.12
seqRun 5 0.95 0.1892 4.78 0.063 0.55
Age 1 0.03 0.0273 0.69 0.002 0.50
Parity 1 0.11 0.1130 2.85 0.008 0.96
BMI 1 0.09 0.0929 2.35 0.006 0.89
HLA_Time_Interaction 1 0.02 0.0184 0.47 0.001 0.97
Residuals 340 13.45 0.0396 0.901 0.80
Total 353 14.93 1.000 8.1.2.3.2 HLA type interaction with time (reference: DRXX)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.85 0.010 0.44
T1Dstatus 1 0.06 0.0608 1.53 0.004 0.45
Days 1 0.07 0.0695 1.76 0.005 0.14
seqRun 5 0.95 0.1892 4.78 0.063 0.57
Age 1 0.03 0.0273 0.69 0.002 0.50
Parity 1 0.11 0.1130 2.85 0.008 0.96
BMI 1 0.09 0.0929 2.35 0.006 0.87
HLA_Time_Interaction 1 0.00 0.0027 0.07 0.000 1.00
Residuals 340 13.47 0.0396 0.902 0.76
Total 353 14.93 1.000 8.1.2.3.3 HLA type interaction with time (reference: Group3o4)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.85 0.010 0.45
T1Dstatus 1 0.06 0.0608 1.54 0.004 0.44
Days 1 0.07 0.0695 1.76 0.005 0.15
seqRun 5 0.95 0.1892 4.78 0.063 0.55
Age 1 0.03 0.0273 0.69 0.002 0.52
Parity 1 0.11 0.1130 2.85 0.008 0.96
BMI 1 0.09 0.0929 2.35 0.006 0.87
HLA_Time_Interaction 1 0.02 0.0161 0.41 0.001 0.99
Residuals 340 13.46 0.0396 0.901 0.80
Total 353 14.93 1.000 8.1.2.3.4 HLA type (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.07 0.0730 1.85 0.005 0.14
seqRun 5 0.92 0.1845 4.67 0.062 0.76
Age 1 0.03 0.0266 0.67 0.002 0.58
Parity 1 0.15 0.1451 3.67 0.010 0.95
BMI 1 0.12 0.1196 3.03 0.008 0.38
T1Dstatus 1 0.05 0.0528 1.34 0.004 0.47
HLA 2 0.12 0.0583 1.48 0.008 0.55
Residuals 341 13.47 0.0395 0.902 0.73
Total 353 14.93 1.000 8.1.2.4 Parity
8.1.2.4.1 Parity interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.86 0.010 0.429
T1Dstatus 1 0.06 0.0608 1.54 0.004 0.408
Days 1 0.07 0.0695 1.76 0.005 0.143
seqRun 5 0.95 0.1892 4.79 0.063 0.569
Age 1 0.03 0.0273 0.69 0.002 0.506
Parity 1 0.11 0.1130 2.86 0.008 0.961
BMI 1 0.09 0.0929 2.36 0.006 0.874
Parity_Time_Interaction 1 0.06 0.0564 1.43 0.004 0.051 .
Residuals 340 13.41 0.0395 0.899 0.568
Total 353 14.93 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.4.2 Parity (no interaction but within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.039 0.0194 0.526 0.019 0.716
T1Dstatus 1 0.015 0.0146 0.397 0.007 0.730
seqRun 1 0.038 0.0383 1.042 0.019 0.247
Age 1 0.102 0.1024 2.782 0.050 0.232
BMI 1 0.014 0.0143 0.388 0.007 0.797
Parity 1 0.053 0.0529 1.439 0.026 0.026 *
Residuals 48 1.766 0.0368 0.871 0.612
Total 55 2.028 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.4.3 Parity (no interaction but within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.09 0.047 1.12 0.014 0.48
T1Dstatus 1 0.03 0.027 0.64 0.004 0.59
seqRun 1 0.33 0.333 7.85 0.048 0.42
Age 1 0.03 0.026 0.61 0.004 0.95
BMI 1 0.01 0.014 0.32 0.002 0.24
Parity 1 0.05 0.050 1.18 0.007 0.93
Residuals 150 6.35 0.042 0.921 0.86
Total 157 6.89 1.000 8.1.2.4.4 Parity (no interaction but within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.10 0.049 1.24 0.016 0.329
T1Dstatus 1 0.04 0.039 1.00 0.007 0.344
seqRun 1 0.38 0.382 9.75 0.064 0.642
Age 1 0.02 0.019 0.48 0.003 0.013 *
BMI 1 0.08 0.075 1.93 0.013 0.808
Parity 1 0.19 0.193 4.94 0.032 0.885
Residuals 132 5.17 0.039 0.865 0.641
Total 139 5.97 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.5 Mode of delivery
8.1.2.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.86 0.010 0.450
T1Dstatus 1 0.06 0.0608 1.54 0.004 0.409
MOD 2 0.12 0.0595 1.50 0.008 0.526
Days 1 0.07 0.0728 1.84 0.005 0.117
seqRun 5 0.92 0.1830 4.63 0.061 0.663
Age 1 0.05 0.0454 1.15 0.003 0.026 *
Parity 1 0.11 0.1141 2.89 0.008 0.908
BMI 1 0.07 0.0660 1.67 0.004 0.949
MOD_Time_Interaction 1 0.02 0.0238 0.60 0.002 0.866
Residuals 338 13.36 0.0395 0.895 0.819
Total 353 14.93 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.5.2 Mode of delivery interaction with time (reference: Elective caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.86 0.010 0.448
T1Dstatus 1 0.06 0.0608 1.54 0.004 0.446
MOD 2 0.12 0.0595 1.50 0.008 0.551
Days 1 0.07 0.0728 1.84 0.005 0.135
seqRun 5 0.92 0.1830 4.63 0.061 0.643
Age 1 0.05 0.0454 1.15 0.003 0.022 *
Parity 1 0.11 0.1141 2.88 0.008 0.921
BMI 1 0.07 0.0660 1.67 0.004 0.960
MOD_Time_Interaction 1 0.02 0.0168 0.43 0.001 0.797
Residuals 338 13.37 0.0396 0.896 0.805
Total 353 14.93 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.5.3 Mode of delivery interaction with time (reference: Labour)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.15 0.0734 1.85 0.010 0.423
T1Dstatus 1 0.06 0.0608 1.54 0.004 0.463
MOD 2 0.12 0.0595 1.50 0.008 0.552
Days 1 0.07 0.0728 1.84 0.005 0.124
seqRun 5 0.92 0.1830 4.62 0.061 0.643
Age 1 0.05 0.0454 1.15 0.003 0.017 *
Parity 1 0.11 0.1141 2.88 0.008 0.913
BMI 1 0.07 0.0660 1.67 0.004 0.964
MOD_Time_Interaction 1 0.01 0.0059 0.15 0.000 1.000
Residuals 338 13.38 0.0396 0.896 0.843
Total 353 14.93 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.5.4 Mode of delivery (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.07 0.0730 1.85 0.005 0.13
seqRun 5 0.92 0.1845 4.67 0.062 0.76
Age 1 0.03 0.0266 0.67 0.002 0.60
Parity 1 0.15 0.1451 3.67 0.010 0.94
BMI 1 0.12 0.1196 3.03 0.008 0.38
HLA 2 0.11 0.0533 1.35 0.007 0.57
T1Dstatus 1 0.06 0.0627 1.59 0.004 0.39
MOD 2 0.08 0.0419 1.06 0.006 0.66
Residuals 339 13.39 0.0395 0.897 0.80
Total 353 14.93 1.000 8.1.2.6 Carbohydrate intake
8.1.2.6.1 Carbohydrate interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.17 0.0831 2.13 0.012 0.40
T1Dstatus 1 0.09 0.0930 2.38 0.007 0.28
Carbs 1 0.09 0.0851 2.18 0.006 0.32
seqRun 5 0.88 0.1755 4.49 0.065 0.78
Tri 2 0.02 0.0091 0.23 0.001 0.82
Age 1 0.03 0.0261 0.67 0.002 0.97
Parity 1 0.13 0.1344 3.44 0.010 0.89
BMI 1 0.05 0.0507 1.30 0.004 0.91
Carb_Time_Interaction 1 0.00 0.0007 0.02 0.000 1.00
Residuals 310 12.12 0.0391 0.893 0.90
Total 325 13.58 1.000 8.1.2.6.2 Carbohydrate interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.17 0.0831 2.16 0.012 0.393
T1Dstatus 1 0.09 0.0930 2.41 0.007 0.295
Carbs 1 0.09 0.0851 2.21 0.006 0.303
seqRun 5 0.88 0.1755 4.55 0.065 0.818
Tri 2 0.02 0.0091 0.24 0.001 0.824
Age 1 0.03 0.0261 0.68 0.002 0.968
Parity 1 0.13 0.1344 3.49 0.010 0.897
BMI 1 0.05 0.0507 1.31 0.004 0.906
Carb_Time_Interaction 1 0.17 0.1743 4.52 0.013 0.002 **
Residuals 310 11.95 0.0386 0.880 0.543
Total 325 13.58 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.6.3 Carbohydrate interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.17 0.0831 2.15 0.012 0.404
T1Dstatus 1 0.09 0.0930 2.40 0.007 0.300
Carbs 1 0.09 0.0851 2.20 0.006 0.342
seqRun 5 0.88 0.1755 4.53 0.065 0.805
Tri 2 0.02 0.0091 0.23 0.001 0.797
Age 1 0.03 0.0261 0.67 0.002 0.963
Parity 1 0.13 0.1344 3.47 0.010 0.903
BMI 1 0.05 0.0507 1.31 0.004 0.899
Carb_Time_Interaction 1 0.12 0.1161 3.00 0.009 0.003 **
Residuals 310 12.01 0.0387 0.885 0.669
Total 325 13.58 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.6.4 Carbohydrate (no interaction within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.158 0.0527 1.710 0.099 0.001 ***
Age 1 0.017 0.0171 0.554 0.011 0.001 ***
Parity 1 0.047 0.0466 1.514 0.029 0.001 ***
BMI 1 0.062 0.0622 2.019 0.039 0.001 ***
HLA 2 0.035 0.0173 0.561 0.022 0.722
T1Dstatus 1 0.053 0.0527 1.710 0.033 0.164
Carbs 1 0.022 0.0225 0.730 0.014 0.479
Residuals 39 1.201 0.0308 0.753 0.531
Total 49 1.595 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.6.5 Carbohydrate (no interaction within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 0.42 0.1059 2.55 0.067 0.001 ***
Age 1 0.06 0.0632 1.52 0.010 0.633
Parity 1 0.10 0.0958 2.30 0.015 0.780
BMI 1 0.01 0.0094 0.23 0.001 0.870
HLA 2 0.07 0.0342 0.82 0.011 0.619
T1Dstatus 1 0.02 0.0203 0.49 0.003 0.695
Carbs 1 0.19 0.1891 4.55 0.030 0.042 *
Residuals 132 5.49 0.0416 0.863 0.288
Total 143 6.36 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.6.6 Carbohydrate (no interaction within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 0.38 0.0943 2.34 0.067 0.89
Age 1 0.02 0.0231 0.57 0.004 0.98
Parity 1 0.13 0.1343 3.33 0.024 0.88
BMI 1 0.09 0.0883 2.19 0.016 0.41
HLA 2 0.06 0.0280 0.70 0.010 0.58
T1Dstatus 1 0.04 0.0435 1.08 0.008 0.33
Carbs 1 0.05 0.0501 1.24 0.009 0.29
Residuals 120 4.84 0.0403 0.862 0.81
Total 131 5.61 1.000 8.1.2.7 Fibre intake
8.1.2.7.1 Fibre interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.17 0.0831 2.13 0.012 0.38
T1Dstatus 1 0.09 0.0930 2.38 0.007 0.32
Fiber 1 0.02 0.0191 0.49 0.001 0.85
seqRun 5 0.97 0.1949 5.00 0.072 0.40
Tri 2 0.02 0.0090 0.23 0.001 0.81
Age 1 0.03 0.0253 0.65 0.002 0.98
Parity 1 0.11 0.1062 2.72 0.008 0.98
BMI 1 0.06 0.0587 1.50 0.004 0.82
Fiber_Time_Interaction 1 0.02 0.0235 0.60 0.002 0.24
Residuals 310 12.09 0.0390 0.891 0.85
Total 325 13.58 1.000 8.1.2.7.2 Fibre interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.17 0.0831 2.15 0.012 0.401
T1Dstatus 1 0.09 0.0930 2.40 0.007 0.285
Fiber 1 0.02 0.0191 0.49 0.001 0.839
seqRun 5 0.97 0.1949 5.03 0.072 0.426
Tri 2 0.02 0.0090 0.23 0.001 0.792
Age 1 0.03 0.0253 0.65 0.002 0.975
Parity 1 0.11 0.1062 2.74 0.008 0.985
BMI 1 0.06 0.0587 1.52 0.004 0.797
Fiber_Time_Interaction 1 0.12 0.1158 2.99 0.009 0.001 ***
Residuals 310 12.00 0.0387 0.884 0.622
Total 325 13.58 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.7.3 Fibre interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.17 0.0831 2.14 0.012 0.423
T1Dstatus 1 0.09 0.0930 2.40 0.007 0.284
Fiber 1 0.02 0.0191 0.49 0.001 0.860
seqRun 5 0.97 0.1949 5.02 0.072 0.389
Tri 2 0.02 0.0090 0.23 0.001 0.832
Age 1 0.03 0.0253 0.65 0.002 0.967
Parity 1 0.11 0.1062 2.74 0.008 0.983
BMI 1 0.06 0.0587 1.51 0.004 0.807
Fiber_Time_Interaction 1 0.08 0.0813 2.10 0.006 0.099 .
Residuals 310 12.03 0.0388 0.886 0.772
Total 325 13.58 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.7.4 Fibre (no interaction within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.158 0.0527 1.714 0.099 0.001 ***
Age 1 0.017 0.0171 0.555 0.011 0.001 ***
Parity 1 0.047 0.0466 1.518 0.029 0.001 ***
BMI 1 0.062 0.0622 2.024 0.039 0.001 ***
HLA 2 0.035 0.0173 0.562 0.022 0.721
T1Dstatus 1 0.053 0.0527 1.714 0.033 0.173
Fiber 1 0.025 0.0252 0.820 0.016 0.433
Residuals 39 1.198 0.0307 0.751 0.513
Total 49 1.595 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.7.5 Fibre (no interaction within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 0.42 0.1059 2.473 0.067 0.001 ***
Age 1 0.06 0.0632 1.477 0.010 0.561
Parity 1 0.10 0.0958 2.237 0.015 0.762
BMI 1 0.01 0.0094 0.220 0.001 0.827
HLA 2 0.07 0.0342 0.799 0.011 0.604
T1Dstatus 1 0.02 0.0203 0.474 0.003 0.657
Fiber 1 0.03 0.0277 0.648 0.004 0.553
Residuals 132 5.65 0.0428 0.889 0.803
Total 143 6.36 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.7.6 Fibre (no interaction within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 0.38 0.0943 2.38 0.067 0.850
Age 1 0.02 0.0231 0.58 0.004 0.979
Parity 1 0.13 0.1343 3.38 0.024 0.870
BMI 1 0.09 0.0883 2.22 0.016 0.444
HLA 2 0.06 0.0280 0.71 0.010 0.586
T1Dstatus 1 0.04 0.0435 1.10 0.008 0.345
Fiber 1 0.12 0.1214 3.06 0.022 0.072 .
Residuals 120 4.76 0.0397 0.850 0.551
Total 131 5.61 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.8 1,5-AG (glucose control measurement)
8.1.2.8.1 1,5-AG interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0814 2.06 0.012 0.392
T1Dstatus 1 0.06 0.0646 1.63 0.005 0.429
Days 1 0.09 0.0908 2.29 0.007 0.031 *
seqRun 4 0.73 0.1826 4.61 0.054 0.362
Age 1 0.03 0.0287 0.72 0.002 0.234
Parity 1 0.10 0.0960 2.42 0.007 0.960
BMI 1 0.11 0.1081 2.73 0.008 0.745
AG15 1 0.04 0.0389 0.98 0.003 0.150
AG15_T1D_Interaction 1 0.01 0.0105 0.27 0.001 0.912
Residuals 311 12.31 0.0396 0.902 0.441
Total 324 13.64 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.8.2 1,5-AG within T1D women
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0327 0.96 0.008 0.715
Days 1 0.06 0.0583 1.71 0.007 0.025 *
seqRun 4 0.67 0.1671 4.91 0.084 0.611
Age 1 0.02 0.0187 0.55 0.002 0.981
Parity 1 0.09 0.0894 2.63 0.011 0.896
BMI 1 0.14 0.1394 4.10 0.018 0.217
AG15 1 0.02 0.0202 0.59 0.003 0.375
Residuals 202 6.87 0.0340 0.866 0.662
Total 213 7.93 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.8.3 1,5-AG interaction with time (within non-T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.29 0.1435 2.853 0.051 0.27
Days 1 0.04 0.0358 0.712 0.006 0.49
seqRun 3 0.19 0.0618 1.230 0.033 0.77
Age 1 0.03 0.0304 0.605 0.005 0.25
Parity 1 0.04 0.0440 0.875 0.008 0.18
BMI 1 0.01 0.0076 0.151 0.001 0.67
AG15 1 0.04 0.0373 0.743 0.007 0.85
Residuals 100 5.03 0.0503 0.889 0.43
Total 110 5.66 1.000 8.1.2.8.4 1,5-AG (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0814 2.06 0.012 0.393
T1Dstatus 1 0.06 0.0646 1.63 0.005 0.427
Days 1 0.09 0.0908 2.30 0.007 0.032 *
seqRun 4 0.73 0.1826 4.62 0.054 0.357
Age 1 0.03 0.0287 0.73 0.002 0.222
Parity 1 0.10 0.0960 2.43 0.007 0.954
BMI 1 0.11 0.1081 2.74 0.008 0.780
AG15 1 0.04 0.0389 0.98 0.003 0.121
Residuals 312 12.32 0.0395 0.903 0.406
Total 324 13.64 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 18.1.2.9 Pre-eclampsia (within T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0341 1.01 0.008 0.71
Days 1 0.03 0.0334 0.99 0.004 0.12
seqRun 4 0.87 0.2164 6.42 0.098 0.46
Age 1 0.02 0.0214 0.63 0.002 0.99
Parity 1 0.11 0.1112 3.30 0.013 0.81
BMI 1 0.13 0.1282 3.81 0.015 0.22
Preeclampsia 1 0.06 0.0629 1.87 0.007 0.64
Residuals 223 7.51 0.0337 0.853 0.75
Total 234 8.80 1.000 8.2 Differential abundance analysis Order taxonomic level
Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type
nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down 0 0 0 0 0 0 1 0 0 0
NotSig 23 23 23 23 22 23 20 23 23 22
Up 0 0 0 0 1 0 2 0 0 1
noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down 0 0 0
NotSig 23 23 23
Up 0 0 08.2.1 Across all trimesters (T1D vs non-T1D)
[1] "No DA taxa"8.2.2 Only Trimester 1 (nonT1D vs T1D)
[1] "No DA taxa"8.2.3 Only Trimester 2 (nonT1D vs T1D)
[1] "No DA taxa"After filtering low prevalent taxa, no species was significantly different between T1D and non-T1D women in this comparison.
8.2.4 Only Trimester 3 (nonT1D vs T1D)
[1] "No DA taxa"8.2.5 T1 vs T2 (T1D and non-T1D data)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Gammaproteobacteria 0.78 0.00202 0.0464 0.088 33.9
2 Gammaproteobacteria 0.78 0.00202 0.0464 0.083 31.6
3 Gammaproteobacteria 0.78 0.00202 0.0464 0.061 27.18.2.6 T2 vs T3 (T1D and non-T1D data)
[1] "No DA taxa"Nothing left after filtering by prevalence and LogFC
8.2.7 T1 vs T3 (T1D and non-T1D data)
Classification LogFC P.Val adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev% T3:mean%
1 Bacilli -0.807 0.00211 0.0243 0.169 55.4 0.268 63.3 0.355
T3Prev%
1 71.48.2.8 T1 vs T2 (in women with T1D)
[1] "No DA taxa"8.2.9 T2 vs T3 (in women with T1D)
[1] "No DA taxa"8.2.10 T1 vs T3 (in women with T1D)
[1] Classification LogFC P.Val adj.P.Val T1:mean%
[6] T1Prev% T3:mean% T3Prev%
<0 rows> (or 0-length row.names)8.2.11 T1 vs T2 (in women without T1D)
[1] "No DA taxa"8.2.12 T2 vs T3 (in women without T1D)
[1] "No DA taxa"8.2.13 T1 vs T3 (in women without T1D)
[1] "No DA taxa"9 Phylum taxonomic level
9.1 Microbial community composition analysis at Phylum level (Beta diversity analysis)
9.1.1 Interaction between T1D status and Time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 5 0.84 0.1678 4.59 0.061 0.79
Days 1 0.10 0.0998 2.73 0.007 0.09 .
T1D_Time_Interaction 1 0.06 0.0557 1.52 0.004 0.16
Age 1 0.02 0.0180 0.49 0.001 0.48
Parity 1 0.15 0.1504 4.11 0.011 0.98
BMI 1 0.11 0.1109 3.03 0.008 0.61
HLA 2 0.11 0.0561 1.53 0.008 0.46
T1Dstatus 1 0.01 0.0061 0.17 0.000 0.93
Residuals 340 12.44 0.0366 0.899 0.73
Total 353 13.83 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1[1] 0.1579.1.2 Other factors
9.1.2.1 Age at conception
9.1.2.1.1 Age at conception interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.15 0.011 0.36
T1Dstatus 1 0.04 0.0436 1.20 0.003 0.52
seqRun 5 0.85 0.1697 4.65 0.061 0.67
Tri 2 0.07 0.0347 0.95 0.005 0.16
Age 1 0.02 0.0169 0.46 0.001 0.89
Parity 1 0.13 0.1302 3.57 0.009 0.98
BMI 1 0.10 0.0996 2.73 0.007 0.80
Age_Time_Interaction 1 0.10 0.1004 2.75 0.007 0.16
Residuals 339 12.36 0.0365 0.894 0.64
Total 353 13.83 1.000 9.1.2.1.2 Age at conception interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.15 0.011 0.39
T1Dstatus 1 0.04 0.0436 1.19 0.003 0.51
seqRun 5 0.85 0.1697 4.65 0.061 0.64
Tri 2 0.07 0.0347 0.95 0.005 0.18
Age 1 0.02 0.0169 0.46 0.001 0.86
Parity 1 0.13 0.1302 3.57 0.009 0.98
BMI 1 0.10 0.0996 2.73 0.007 0.79
Age_Time_Interaction 1 0.09 0.0892 2.44 0.006 0.18
Residuals 339 12.38 0.0365 0.895 0.65
Total 353 13.83 1.000 9.1.2.1.3 Age at conception interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.13 0.011 0.36
T1Dstatus 1 0.04 0.0436 1.19 0.003 0.49
seqRun 5 0.85 0.1697 4.62 0.061 0.65
Tri 2 0.07 0.0347 0.95 0.005 0.16
Age 1 0.02 0.0169 0.46 0.001 0.85
Parity 1 0.13 0.1302 3.54 0.009 0.98
BMI 1 0.10 0.0996 2.71 0.007 0.80
Age_Time_Interaction 1 0.01 0.0073 0.20 0.001 0.66
Residuals 339 12.46 0.0367 0.901 0.78
Total 353 13.83 1.000 9.1.2.1.4 Age at conception (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.14 0.011 0.36
T1Dstatus 1 0.04 0.0436 1.19 0.003 0.49
seqRun 5 0.85 0.1697 4.63 0.061 0.67
Tri 2 0.07 0.0347 0.95 0.005 0.18
Parity 1 0.13 0.1302 3.55 0.009 0.98
BMI 1 0.10 0.0989 2.70 0.007 0.81
Age 1 0.02 0.0176 0.48 0.001 0.34
Residuals 340 12.46 0.0367 0.901 0.78
Total 353 13.83 1.000 9.1.2.2 Body max index (BMI)
9.1.2.2.1 BMI interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.13 0.011 0.38
T1Dstatus 1 0.04 0.0436 1.19 0.003 0.49
seqRun 5 0.85 0.1697 4.62 0.061 0.68
Tri 2 0.07 0.0347 0.95 0.005 0.16
Age 1 0.02 0.0169 0.46 0.001 0.88
Parity 1 0.13 0.1302 3.54 0.009 0.98
BMI 1 0.10 0.0996 2.71 0.007 0.77
BMI_Time_Interaction 1 0.01 0.0061 0.17 0.000 0.88
Residuals 339 12.46 0.0368 0.901 0.85
Total 353 13.83 1.000 9.1.2.2.2 BMI interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.14 0.011 0.34
T1Dstatus 1 0.04 0.0436 1.19 0.003 0.51
seqRun 5 0.85 0.1697 4.63 0.061 0.65
Tri 2 0.07 0.0347 0.95 0.005 0.17
Age 1 0.02 0.0169 0.46 0.001 0.88
Parity 1 0.13 0.1302 3.55 0.009 0.98
BMI 1 0.10 0.0996 2.72 0.007 0.80
BMI_Time_Interaction 1 0.04 0.0411 1.12 0.003 0.54
Residuals 339 12.42 0.0366 0.898 0.78
Total 353 13.83 1.000 9.1.2.2.3 BMI (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.14 0.011 0.40
T1Dstatus 1 0.04 0.0436 1.19 0.003 0.45
seqRun 5 0.85 0.1697 4.63 0.061 0.63
Tri 2 0.07 0.0347 0.95 0.005 0.18
Age 1 0.02 0.0169 0.46 0.001 0.86
Parity 1 0.13 0.1302 3.55 0.009 0.98
BMI 1 0.10 0.0996 2.72 0.007 0.80
BMI_Time_Interaction 1 0.04 0.0351 0.96 0.003 0.15
Residuals 339 12.43 0.0367 0.899 0.73
Total 353 13.83 1.000 9.1.2.2.4 BMI (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.14 0.011 0.38
T1Dstatus 1 0.04 0.0436 1.19 0.003 0.51
seqRun 5 0.85 0.1697 4.63 0.061 0.65
Tri 2 0.07 0.0347 0.95 0.005 0.17
Age 1 0.02 0.0169 0.46 0.001 0.88
Parity 1 0.13 0.1302 3.55 0.009 0.97
BMI 1 0.10 0.0996 2.72 0.007 0.79
Residuals 340 12.46 0.0367 0.901 0.76
Total 353 13.83 1.000 9.1.2.3 HLA type
9.1.2.3.1 HLA type interaction with time (reference: DR34 )
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.14 0.011 0.37
T1Dstatus 1 0.04 0.0436 1.19 0.003 0.50
Days 1 0.07 0.0747 2.04 0.005 0.11
seqRun 5 0.88 0.1760 4.81 0.064 0.56
Age 1 0.02 0.0163 0.44 0.001 0.89
Parity 1 0.13 0.1250 3.42 0.009 0.98
BMI 1 0.10 0.0955 2.61 0.007 0.87
HLA_Time_Interaction 1 0.01 0.0098 0.27 0.001 0.99
Residuals 340 12.43 0.0366 0.899 0.81
Total 353 13.83 1.000 9.1.2.3.2 HLA type interaction with time (reference: DRXX)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.14 0.011 0.35
T1Dstatus 1 0.04 0.0436 1.19 0.003 0.52
Days 1 0.07 0.0747 2.04 0.005 0.13
seqRun 5 0.88 0.1760 4.81 0.064 0.58
Age 1 0.02 0.0163 0.44 0.001 0.90
Parity 1 0.13 0.1250 3.42 0.009 0.97
BMI 1 0.10 0.0955 2.61 0.007 0.85
HLA_Time_Interaction 1 0.00 0.0018 0.05 0.000 1.00
Residuals 340 12.44 0.0366 0.899 0.75
Total 353 13.83 1.000 9.1.2.3.3 HLA type interaction with time (reference: Group3o4)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.14 0.011 0.38
T1Dstatus 1 0.04 0.0436 1.19 0.003 0.51
Days 1 0.07 0.0747 2.04 0.005 0.13
seqRun 5 0.88 0.1760 4.81 0.064 0.56
Age 1 0.02 0.0163 0.44 0.001 0.90
Parity 1 0.13 0.1250 3.42 0.009 0.98
BMI 1 0.10 0.0955 2.61 0.007 0.85
HLA_Time_Interaction 1 0.01 0.0090 0.25 0.001 1.00
Residuals 340 12.43 0.0366 0.899 0.81
Total 353 13.83 1.000 9.1.2.3.4 HLA type (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.08 0.0779 2.14 0.006 0.12
seqRun 5 0.86 0.1722 4.72 0.062 0.74
Age 1 0.02 0.0208 0.57 0.002 0.43
Parity 1 0.17 0.1673 4.59 0.012 0.93
BMI 1 0.12 0.1202 3.29 0.009 0.39
T1Dstatus 1 0.03 0.0303 0.83 0.002 0.58
HLA 2 0.11 0.0572 1.57 0.008 0.50
Residuals 341 12.44 0.0365 0.899 0.71
Total 353 13.83 1.000 9.1.2.4 Parity
9.1.2.4.1 Parity interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.15 0.011 0.356
T1Dstatus 1 0.04 0.0436 1.20 0.003 0.477
Days 1 0.07 0.0747 2.05 0.005 0.128
seqRun 5 0.88 0.1760 4.83 0.064 0.565
Age 1 0.02 0.0163 0.45 0.001 0.905
Parity 1 0.13 0.1250 3.43 0.009 0.976
BMI 1 0.10 0.0955 2.62 0.007 0.856
Parity_Time_Interaction 1 0.04 0.0449 1.23 0.003 0.088 .
Residuals 340 12.39 0.0365 0.896 0.587
Total 353 13.83 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.2.4.2 Parity (no interaction but within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.025 0.0124 0.376 0.014 0.78
T1Dstatus 1 0.003 0.0033 0.102 0.002 0.94
seqRun 1 0.032 0.0325 0.986 0.018 0.21
Age 1 0.093 0.0929 2.819 0.052 0.31
BMI 1 0.020 0.0198 0.601 0.011 0.72
Parity 1 0.037 0.0366 1.111 0.020 0.12
Residuals 48 1.581 0.0329 0.883 0.83
Total 55 1.791 1.000 9.1.2.4.3 Parity (no interaction but within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.10 0.048 1.22 0.015 0.43
T1Dstatus 1 0.02 0.018 0.46 0.003 0.68
seqRun 1 0.33 0.329 8.41 0.051 0.40
Age 1 0.03 0.026 0.68 0.004 0.96
BMI 1 0.02 0.015 0.39 0.002 0.21
Parity 1 0.06 0.062 1.58 0.010 0.94
Residuals 150 5.87 0.039 0.915 0.86
Total 157 6.41 1.000 9.1.2.4.4 Parity (no interaction but within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.10 0.050 1.37 0.018 0.302
T1Dstatus 1 0.03 0.030 0.82 0.005 0.407
seqRun 1 0.38 0.378 10.36 0.068 0.632
Age 1 0.01 0.014 0.38 0.002 0.031 *
BMI 1 0.07 0.069 1.90 0.012 0.793
Parity 1 0.18 0.184 5.05 0.033 0.899
Residuals 132 4.81 0.036 0.861 0.656
Total 139 5.59 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.2.5 Mode of delivery
9.1.2.5.1 Mode of delivery interaction with time (reference: Emergency caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.14 0.011 0.37
T1Dstatus 1 0.04 0.0436 1.19 0.003 0.48
MOD 2 0.10 0.0485 1.33 0.007 0.58
Days 1 0.08 0.0780 2.13 0.006 0.11
seqRun 5 0.85 0.1699 4.64 0.061 0.67
Age 1 0.03 0.0296 0.81 0.002 0.13
Parity 1 0.12 0.1235 3.37 0.009 0.94
BMI 1 0.07 0.0651 1.78 0.005 0.95
MOD_Time_Interaction 1 0.02 0.0150 0.41 0.001 0.65
Residuals 338 12.37 0.0366 0.895 0.83
Total 353 13.83 1.000 9.1.2.5.2 Mode of delivery interaction with time (reference: Elective caesarea)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.14 0.011 0.38
T1Dstatus 1 0.04 0.0436 1.19 0.003 0.52
MOD 2 0.10 0.0485 1.32 0.007 0.59
Days 1 0.08 0.0780 2.13 0.006 0.12
seqRun 5 0.85 0.1699 4.64 0.061 0.66
Age 1 0.03 0.0296 0.81 0.002 0.12
Parity 1 0.12 0.1235 3.37 0.009 0.95
BMI 1 0.07 0.0651 1.78 0.005 0.96
MOD_Time_Interaction 1 0.01 0.0118 0.32 0.001 0.63
Residuals 338 12.37 0.0366 0.895 0.82
Total 353 13.83 1.000 9.1.2.5.3 Mode of delivery interaction with time (reference: Labour)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.16 0.0783 2.14 0.011 0.36
T1Dstatus 1 0.04 0.0436 1.19 0.003 0.52
MOD 2 0.10 0.0485 1.32 0.007 0.58
Days 1 0.08 0.0780 2.13 0.006 0.12
seqRun 5 0.85 0.1699 4.64 0.061 0.65
Age 1 0.03 0.0296 0.81 0.002 0.10
Parity 1 0.12 0.1235 3.37 0.009 0.95
BMI 1 0.07 0.0651 1.78 0.005 0.96
MOD_Time_Interaction 1 0.00 0.0024 0.07 0.000 1.00
Residuals 338 12.38 0.0366 0.895 0.86
Total 353 13.83 1.000 9.1.2.5.4 Mode of delivery (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
Days 1 0.08 0.0779 2.13 0.006 0.11
seqRun 5 0.86 0.1722 4.71 0.062 0.73
Age 1 0.02 0.0208 0.57 0.002 0.44
Parity 1 0.17 0.1673 4.58 0.012 0.93
BMI 1 0.12 0.1202 3.29 0.009 0.38
HLA 2 0.10 0.0516 1.41 0.007 0.53
T1Dstatus 1 0.04 0.0416 1.14 0.003 0.47
MOD 2 0.05 0.0256 0.70 0.004 0.77
Residuals 339 12.39 0.0365 0.896 0.83
Total 353 13.83 1.000 9.1.2.6 Carbohydrate intake
9.1.2.6.1 Carbohydrate interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.17 0.0862 2.40 0.014 0.33
T1Dstatus 1 0.07 0.0725 2.02 0.006 0.33
Carbs 1 0.08 0.0759 2.11 0.006 0.33
seqRun 5 0.81 0.1623 4.52 0.065 0.78
Tri 2 0.02 0.0086 0.24 0.001 0.72
Age 1 0.02 0.0220 0.61 0.002 0.98
Parity 1 0.15 0.1522 4.24 0.012 0.92
BMI 1 0.05 0.0539 1.50 0.004 0.89
Carb_Time_Interaction 1 0.00 -0.0035 -0.10 0.000 1.00
Residuals 310 11.14 0.0359 0.890 0.90
Total 325 12.51 1.000 9.1.2.6.2 Carbohydrate interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.17 0.0862 2.44 0.014 0.324
T1Dstatus 1 0.07 0.0725 2.05 0.006 0.355
Carbs 1 0.08 0.0759 2.14 0.006 0.316
seqRun 5 0.81 0.1623 4.59 0.065 0.819
Tri 2 0.02 0.0086 0.24 0.001 0.735
Age 1 0.02 0.0220 0.62 0.002 0.982
Parity 1 0.15 0.1522 4.30 0.012 0.919
BMI 1 0.05 0.0539 1.53 0.004 0.884
Carb_Time_Interaction 1 0.17 0.1693 4.79 0.014 0.002 **
Residuals 310 10.97 0.0354 0.876 0.554
Total 325 12.51 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.2.6.3 Carbohydrate interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.17 0.0862 2.42 0.014 0.351
T1Dstatus 1 0.07 0.0725 2.04 0.006 0.346
Carbs 1 0.08 0.0759 2.13 0.006 0.339
seqRun 5 0.81 0.1623 4.57 0.065 0.806
Tri 2 0.02 0.0086 0.24 0.001 0.708
Age 1 0.02 0.0220 0.62 0.002 0.982
Parity 1 0.15 0.1522 4.28 0.012 0.912
BMI 1 0.05 0.0539 1.52 0.004 0.880
Carb_Time_Interaction 1 0.12 0.1178 3.31 0.009 0.003 **
Residuals 310 11.02 0.0355 0.880 0.660
Total 325 12.51 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.2.6.4 Carbohydrate (no interaction within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.144 0.0479 1.746 0.104 0.75
Age 1 0.015 0.0153 0.557 0.011 0.75
Parity 1 0.041 0.0410 1.495 0.030 0.75
BMI 1 0.064 0.0645 2.351 0.047 0.75
HLA 2 0.020 0.0102 0.372 0.015 0.79
T1Dstatus 1 0.028 0.0281 1.024 0.020 0.32
Carbs 1 0.003 0.0026 0.095 0.002 0.93
Residuals 39 1.070 0.0274 0.772 0.86
Total 49 1.386 1.000 9.1.2.6.5 Carbohydrate (no interaction within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 0.38 0.0948 2.47 0.064 0.002 **
Age 1 0.06 0.0624 1.63 0.011 0.591
Parity 1 0.12 0.1156 3.01 0.020 0.825
BMI 1 0.01 0.0120 0.31 0.002 0.512
HLA 2 0.06 0.0285 0.74 0.010 0.635
T1Dstatus 1 0.01 0.0145 0.38 0.002 0.729
Carbs 1 0.18 0.1823 4.75 0.031 0.041 *
Residuals 132 5.07 0.0384 0.860 0.294
Total 143 5.89 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.2.6.6 Carbohydrate (no interaction within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 0.36 0.0896 2.39 0.069 0.72
Age 1 0.02 0.0214 0.57 0.004 0.98
Parity 1 0.13 0.1286 3.43 0.025 0.87
BMI 1 0.08 0.0792 2.11 0.015 0.41
HLA 2 0.06 0.0279 0.74 0.011 0.54
T1Dstatus 1 0.03 0.0322 0.86 0.006 0.39
Carbs 1 0.05 0.0495 1.32 0.009 0.27
Residuals 120 4.50 0.0375 0.861 0.81
Total 131 5.23 1.000 9.1.2.7 Fibre intake
9.1.2.7.1 Fibre interaction with time (reference: trimester 1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.17 0.0862 2.40 0.014 0.33
T1Dstatus 1 0.07 0.0725 2.02 0.006 0.36
Fiber 1 0.00 0.0038 0.11 0.000 0.96
seqRun 5 0.90 0.1809 5.04 0.072 0.43
Tri 2 0.02 0.0083 0.23 0.001 0.71
Age 1 0.02 0.0215 0.60 0.002 0.99
Parity 1 0.12 0.1207 3.37 0.010 0.99
BMI 1 0.06 0.0618 1.72 0.005 0.80
Fiber_Time_Interaction 1 0.02 0.0193 0.54 0.002 0.22
Residuals 310 11.12 0.0359 0.889 0.88
Total 325 12.51 1.000 9.1.2.7.2 Fibre interaction with time (reference: trimester 2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.17 0.0862 2.42 0.014 0.345
T1Dstatus 1 0.07 0.0725 2.04 0.006 0.352
Fiber 1 0.00 0.0038 0.11 0.000 0.971
seqRun 5 0.90 0.1809 5.08 0.072 0.452
Tri 2 0.02 0.0083 0.23 0.001 0.701
Age 1 0.02 0.0215 0.60 0.002 0.985
Parity 1 0.12 0.1207 3.39 0.010 0.991
BMI 1 0.06 0.0618 1.74 0.005 0.772
Fiber_Time_Interaction 1 0.10 0.1044 2.93 0.008 0.002 **
Residuals 310 11.03 0.0356 0.882 0.691
Total 325 12.51 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.2.7.3 Fibre interaction with time (reference: trimester 3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.17 0.0862 2.42 0.014 0.364
T1Dstatus 1 0.07 0.0725 2.03 0.006 0.335
Fiber 1 0.00 0.0038 0.11 0.000 0.971
seqRun 5 0.90 0.1809 5.07 0.072 0.414
Tri 2 0.02 0.0083 0.23 0.001 0.745
Age 1 0.02 0.0215 0.60 0.002 0.978
Parity 1 0.12 0.1207 3.38 0.010 0.987
BMI 1 0.06 0.0618 1.73 0.005 0.782
Fiber_Time_Interaction 1 0.08 0.0804 2.26 0.006 0.075 .
Residuals 310 11.06 0.0357 0.884 0.797
Total 325 12.51 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.2.7.4 Fibre (no interaction within T1)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 3 0.144 0.0479 1.745 0.104 0.006 **
Age 1 0.015 0.0153 0.557 0.011 0.006 **
Parity 1 0.041 0.0410 1.495 0.030 0.006 **
BMI 1 0.064 0.0645 2.350 0.047 0.006 **
HLA 2 0.020 0.0102 0.372 0.015 0.797
T1Dstatus 1 0.028 0.0281 1.023 0.020 0.325
Fiber 1 0.002 0.0023 0.083 0.002 0.934
Residuals 39 1.070 0.0274 0.772 0.829
Total 49 1.386 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.2.7.5 Fibre (no interaction within T2)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 0.38 0.0948 2.392 0.064 0.001 ***
Age 1 0.06 0.0624 1.573 0.011 0.561
Parity 1 0.12 0.1156 2.916 0.020 0.845
BMI 1 0.01 0.0120 0.303 0.002 0.514
HLA 2 0.06 0.0285 0.718 0.010 0.622
T1Dstatus 1 0.01 0.0145 0.366 0.002 0.705
Fiber 1 0.01 0.0145 0.367 0.002 0.721
Residuals 132 5.23 0.0396 0.889 0.869
Total 143 5.89 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.2.7.6 Fibre (no interaction within T3)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
seqRun 4 0.36 0.0896 2.43 0.069 0.658
Age 1 0.02 0.0214 0.58 0.004 0.975
Parity 1 0.13 0.1286 3.48 0.025 0.846
BMI 1 0.08 0.0792 2.14 0.015 0.440
HLA 2 0.06 0.0279 0.75 0.011 0.541
T1Dstatus 1 0.03 0.0322 0.87 0.006 0.404
Fiber 1 0.12 0.1151 3.11 0.022 0.074 .
Residuals 120 4.44 0.0370 0.849 0.572
Total 131 5.23 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.2.8 1,5-AG (glucose control measurement)
9.1.2.8.1 1,5-AG interaction with time
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.18 0.0883 2.42 0.014 0.318
T1Dstatus 1 0.05 0.0462 1.26 0.004 0.509
Days 1 0.10 0.0982 2.69 0.008 0.028 *
seqRun 4 0.67 0.1677 4.59 0.053 0.393
Age 1 0.01 0.0135 0.37 0.001 0.636
Parity 1 0.11 0.1118 3.06 0.009 0.975
BMI 1 0.11 0.1111 3.04 0.009 0.731
AG15 1 0.03 0.0312 0.85 0.002 0.061 .
AG15_T1D_Interaction 1 0.01 0.0101 0.28 0.001 0.839
Residuals 311 11.37 0.0366 0.900 0.403
Total 324 12.64 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.2.8.2 1,5-AG within T1D women
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.07 0.0355 1.15 0.010 0.591
Days 1 0.06 0.0611 1.97 0.008 0.017 *
seqRun 4 0.62 0.1558 5.03 0.086 0.646
Age 1 0.00 0.0049 0.16 0.001 0.963
Parity 1 0.10 0.1028 3.32 0.014 0.881
BMI 1 0.14 0.1427 4.61 0.020 0.203
AG15 1 0.02 0.0162 0.52 0.002 0.360
Residuals 202 6.25 0.0309 0.860 0.536
Total 213 7.27 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.2.8.3 1,5-AG interaction with time (within non-T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.26 0.1302 2.723 0.049 0.29
Days 1 0.04 0.0369 0.772 0.007 0.47
seqRun 3 0.15 0.0513 1.072 0.029 0.64
Age 1 0.03 0.0276 0.577 0.005 0.23
Parity 1 0.04 0.0366 0.765 0.007 0.51
BMI 1 0.01 0.0064 0.133 0.001 0.68
AG15 1 0.03 0.0314 0.656 0.006 0.87
Residuals 100 4.78 0.0478 0.896 0.46
Total 110 5.33 1.000 9.1.2.8.4 1,5-AG (no interaction)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.18 0.0883 2.42 0.014 0.323
T1Dstatus 1 0.05 0.0462 1.27 0.004 0.496
Days 1 0.10 0.0982 2.69 0.008 0.030 *
seqRun 4 0.67 0.1677 4.60 0.053 0.383
Age 1 0.01 0.0135 0.37 0.001 0.665
Parity 1 0.11 0.1118 3.06 0.009 0.977
BMI 1 0.11 0.1111 3.05 0.009 0.764
AG15 1 0.03 0.0312 0.85 0.002 0.058 .
Residuals 312 11.38 0.0365 0.900 0.362
Total 324 12.64 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.1.2.9 Pre-eclampsia (within T1D women)
Call:
adonis(formula = D ~ ., data = mtdat[, metadata_order, drop = F], permutations = 0)
Permutation: free
Number of permutations: 0
Terms added sequentially (first to last)
Df SumsOfSqs MeanSqs F.Model R2 Pr(>F)
HLA 2 0.08 0.0389 1.27 0.010 0.61
Days 1 0.04 0.0357 1.17 0.004 0.09 .
seqRun 4 0.81 0.2031 6.63 0.101 0.51
Age 1 0.01 0.0082 0.27 0.001 0.99
Parity 1 0.13 0.1284 4.20 0.016 0.79
BMI 1 0.13 0.1316 4.30 0.016 0.20
Preeclampsia 1 0.06 0.0571 1.86 0.007 0.63
Residuals 223 6.83 0.0306 0.845 0.65
Total 234 8.08 1.000
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 19.2 Differential abundance analysis Phylum taxonomic level
Controlling for multiple measurements, sequencing run, conception age, BMI, parity and HLA type
nonT1D_vs_T1D T1 T2 T3 T1_vs_T2 T2_vs_T3 T1_vs_T3 T1DT1vsT2 T1DT2vsT3 T1DT1vsT3
Down 0 0 0 0 0 0 0 1 0 1
NotSig 11 11 11 11 11 11 11 10 11 10
Up 0 0 0 0 0 0 0 0 0 0
noT1DT1vsT2 noT1DT2vsT3 noT1DT1vsT3
Down 0 0 0
NotSig 11 11 11
Up 0 0 09.2.1 Across all trimesters (T1D vs non-T1D)
[1] "No DA taxa"9.2.2 Only Trimester 1 (nonT1D vs T1D)
[1] "No DA taxa"9.2.3 Only Trimester 2 (nonT1D vs T1D)
[1] "No DA taxa"After filtering low prevalent taxa, no species was significantly different between T1D and non-T1D women in this comparison.
9.2.4 Only Trimester 3 (nonT1D vs T1D)
[1] "No DA taxa"9.2.5 T1 vs T2 (T1D and non-T1D data)
[1] "No DA taxa"9.2.6 T2 vs T3 (T1D and non-T1D data)
[1] "No DA taxa"Nothing left after filtering by prevalence and LogFC
9.2.7 T1 vs T3 (T1D and non-T1D data)
[1] "No DA taxa"9.2.8 T1 vs T2 (in women with T1D)
Classification LogFC P.Val adj.P.Val T1:mean% T1Prev% T2:mean% T2Prev%
1 Bacteroidetes -0.634 0.000461 0.00507 52.3 97.4 55.1 1009.2.9 T2 vs T3 (in women with T1D)
[1] "No DA taxa"9.2.10 T1 vs T3 (in women with T1D)
Classification LogFC P.Val adj.P.Val mean% Prev%
1 Bacteroidetes -0.589 0.00113 0.0124 52.3 97.4
2 Bacteroidetes -0.589 0.00113 0.0124 55.9 100.09.2.11 T1 vs T2 (in women without T1D)
[1] "No DA taxa"9.2.12 T2 vs T3 (in women without T1D)
[1] "No DA taxa"9.2.13 T1 vs T3 (in women without T1D)
[1] "No DA taxa"